Machine Learning means using data and algorithms to build intelligent systems. There are various Machine Learning algorithms used for training models that help in solving problems and building intelligent systems. While learning Machine Learning, many people are often confused about…
In Machine Learning, Feature Selection is the process of choosing a subset of relevant and significant features (variables or attributes) from features available in a dataset. The goal of selecting features is to improve the performance of a Machine Learning…
Data Visualization is a critical aspect of data science and analytics. It refers to presenting data in graphical or visual formats, such as charts, graphs, and maps, to help people understand the patterns, trends, and insights hidden within large and…
Customer Acquisition Cost (CAC) Analysis is a critical aspect of business strategy where Data Science plays a vital role. CAC refers to the cost a company incurs to acquire a new customer. Understanding and optimizing this cost is crucial for…
“Machine Learning Algorithms: Handbook” is a book based on a step by step guide to all Machine Learning algorithms with implementation using Python. In this article, I’ll give you a complete overview of the book so that you can understand…
Many people find solving a Data Science problem difficult even after mastering Machine Learning algorithms. The problem is that they focus more on algorithms than skills and the mindset of working with data. Data Science is not all about mastering…
Data manipulation is a fundamental process in data science that involves making changes, transformations, or adjustments to raw data to prepare it for analysis. This process is critical because real-world data is often messy, incomplete, or in a format that…
Cloud platforms, also known as cloud computing platforms, are comprehensive services provided by technology companies like Amazon, Microsoft, Google, and IBM, among others. These platforms offer a wide range of computing resources, including servers, storage, databases, networking, analytics, Machine Learning,…
Air quality index (AQI) analysis is a crucial aspect of environmental data science that involves monitoring and analyzing air quality in a specific location. It aims to provide a numerical value representative of overall air quality, essential for public health…
Domain knowledge refers to expertise and understanding of a specific field or subject matter. It encompasses the concepts, terminology, practices, and challenges associated with that domain. In Data Science, domain knowledge means a deep understanding of the industry, business, or…
Feature Engineering is a critical step in solving a Data Science problem that involves creating or selecting the most relevant and informative features (input variables) from raw data. These features are then used to train machine learning models, so the…
Data storytelling is a compelling way of communicating insights and information derived from data by constructing a narrative around it. It involves presenting data-driven findings in a clear, engaging, and relatable manner, similar to how a storyteller weaves a tale.…
Dating Recommendation refers to using data-driven techniques to provide personalized matchmaking suggestions to individuals seeking partners through online dating platforms. These recommendations are based on various factors and preferences, aiming to increase the likelihood of successful and compatible matches. If…
In Data Science interviews, technical questions are designed to assess your fundamentals of working with data and your understanding of using Data Science concepts in a given problem. If you want to understand what types of questions are asked in…
In Machine Learning, Ridge and Lasso Regression are regularization techniques used in linear regression to prevent overfitting and improve the model’s generalization to unseen data. They work by adding a penalty term to the linear regression loss function. If you…
Everyone has their own way of approaching a Data Science problem. If you are a beginner in Data Science, then your way of approaching the problem will develop over time. But there are some steps you should follow to start…
Fitness Watch Data Analysis involves analyzing the data collected by fitness wearables or smartwatches to gain insights into users’ health and activity patterns. These devices track metrics like steps taken, energy burned, walking speed, and more. So, if you want…
Questions like User Engagement Analysis are popular SQL questions in Data Science interviews. To solve this problem, you have to analyze user engagement to find the most engaging posts and users based on the given conditions. So, if you want…
Machine Learning means using data and algorithms to build intelligent systems. Machine Learning algorithms are computational procedures that enable machines to learn patterns and relationships from data without being explicitly programmed. These algorithms allow machines to make predictions, decisions, and…
Supply Chain involves coordination among various entities, such as suppliers, manufacturers, distributors, retailers, and customers, to optimize the process to minimize costs, enhance quality, and meet customer demands. If you are aiming for a Data Science job in retail, manufacturing, logistics,…
Demand Forecasting means estimating future customer demand for a product or service based on historical data and relevant factors. Inventory Optimization is the strategic management of inventory levels to ensure that the right amount of goods is available at the…
While learning Data Science, the decision between pursuing a degree or opting for courses and certifications can significantly impact your career trajectory. Your educational background plays a crucial role in determining the most suitable path for your journey in data…
In the Finance industry, various institutions and entities come together to facilitate financial transactions, manage risks, allocate resources, and make informed decisions, including commercial banks, investment banks, asset management firms, insurance companies, stock exchanges, regulatory bodies, and more. If you…
Python is a popular programming language for Data Analysis for several reasons. In the same way, Tableau and Power BI are powerful tools used in the industry for Data Analysis. It confuses a lot of people, especially beginners, why we…
Anomaly detection in transactions means identifying unusual or unexpected patterns within transactions or related activities. These patterns, known as anomalies or outliers, deviate significantly from the expected norm and could indicate irregular or fraudulent behaviour. If you want to learn…
Questions like Sales by Day of the Week Report are popular SQL questions in Data Science interviews. To solve this problem, you need to group the sales data by the day of the week, calculate the total sales amount for…
Marketing is a strategic and dynamic process to promote products or services to a target audience. It involves activities that create awareness, generate interest, and influence consumer behaviour. If you are aiming to work as a Data Science professional in…
Hyperparameter tuning is an essential process in Machine Learning that involves optimizing the settings that guide the training of a Machine Learning model. But these settings themselves are not learned from the data. These settings, called hyperparameters, play a vital…
A Web Data ETL (Extract, Transform, Load) pipeline is a systematic process used in data engineering to collect, transform, and load data from various sources on the internet into a structured and usable format for analysis and storage. So, if…
Questions like grouping sold products by date are popular SQL questions in Data Science interviews. In this problem, your task is to group the products sold on each date and calculate the total number of products sold on that date.…
In Data Science, time series refers to a sequence of data points recorded at specific time intervals. Time series data captures observations over time, where each data point corresponds to a particular moment or period. Time series analysis involves uncovering…
Data cleaning, also known as data cleansing or scrubbing, is a crucial step in data preparation and analysis. It refers to the systematic and meticulous identification, correction, and removal of errors, inconsistencies, and inaccuracies from data. The main objective of…
Forecasting the number of subscriptions Netflix will achieve in a time period is a vital business practice that enables them to plan, strategize, and make data-driven decisions. It enhances operational efficiency, financial planning, and content strategy, ultimately contributing to their…
In today’s competitive Data Science field, employers prefer candidates who can seamlessly bridge the gap between working with data and domain knowledge. By delving into projects that align with specific industries, you can demonstrate a deep understanding of the domain’s…
Questions like calculating the average selling price of various products are popular SQL questions in Data Science interviews. The average selling price is calculated by adding up all the selling prices of a specific product and dividing the total by…
Plotly is a powerful and versatile data visualization library used by Data Science professionals to create interactive and visually appealing plots, charts, and graphs. It enables users to represent complex datasets in a graphical form, making it easier to comprehend…
If you are looking for your first data science job, you need advanced and unique projects mentioned in your resume. A data science professional works with APIs to collect real-time data from company databases and third-party applications. Having at least…
A Music Recommendation System is an application of Data Science that aims to assist users in discovering new and relevant musical content based on their preferences and listening behaviour. Personalized music recommendations have become an essential tool in the digital…
Data analysis is the systematic process of inspecting, cleaning, transforming, and interpreting raw data to uncover meaningful patterns, trends, and insights. A data analyst is a Data Science professional skilled in working with data and equipped with the necessary tools…
Outliers are data points that deviate significantly from the rest of the data. These data points lie far away from the majority of the data points and can have a substantial impact on statistical analysis and modelling. If you want…
Recommendation systems are one of the popular applications of Data Science in every domain. The recommendation system of Amazon works by using both collaborative filtering and content-based filtering techniques. Amazon uses collaborative filtering to analyze user behaviour and recommend products…
Many web platforms and applications perform A/B testing to run experiments to find the best design, layout, or themes for their platform. Instead of relying on assumptions or hunches, applications and websites can test different design variations on real-time users…
Data Analysis means understanding the story behind the numbers. It is a systematic process of examining, cleaning, transforming, and interpreting raw data to uncover the story behind the data points. If you are learning Data Analysis, one of the best…
Neural Networks are a type of computational model inspired by the structure and functioning of a human brain. They are composed of interconnected nodes called neurons, organized into layers. Each neuron receives inputs, processes them, and produces an output that…
SQL is widely used in Data Science because it allows data science professionals to extract and manipulate data efficiently from databases. It is a powerful language for managing and analyzing structured data. If you are looking for some practical SQL…
Bank Account Summary is a popular SQL question in Data Science interviews. It involves generating a bank account summary in a specific format using SQL. So, if you want to know how to create a bank account summary, this article…
Matplotlib is a popular data visualization library for Python. It provides functions and tools enabling data scientists to create various plots and charts. Matplotlib allows data scientists to create high-quality visualizations that effectively communicate insights and patterns hidden within the…
Next Word Prediction means predicting the most likely word or phrase that will come next in a sentence or text. It is like having an inbuilt feature on an application that suggests the next word as you type or speak.…
A Machine Learning Engineer uses data and algorithms to build intelligent systems. If you are new to machine learning, you need to work on beginner-level machine learning projects to understand how to use machine learning algorithms on datasets to solve problems. If…
Python and R are preferred languages for data science due to their rich ecosystem of libraries, extensive community support, and powerful tools for statistical analysis, data manipulation, machine learning, and visualization. You can choose either Python or R for Data…
Calculating Ride Cancellation Rate is a popular SQL question in Data Science interviews. It involves analyzing the cancellation rate for ride requests, specifically from users who are not banned. So, if you want to know how to calculate the ride…
Pandas is a powerful open-source library in Python that provides high-performance data manipulation and analysis tools. Pandas enhances the productivity and efficiency of Data Science professionals by providing a comprehensive set of tools for data manipulation, analysis, and exploration. Its…
User Engagement Analysis is a data-driven approach to assess and understand user involvement, interaction, and satisfaction with a product, service, or platform. It involves analyzing various metrics and behavioural patterns to gain insights into user behaviour and preferences. It aids…
Data Engineering focuses on the foundational aspects of managing and processing data, providing the necessary infrastructure and pipelines to support Machine Learning and Analytics workflows. It ensures that data is reliable, accessible, and processed efficiently to enable data-driven decision-making and…
Market Analysis is a popular SQL question in Data Science interviews. It is often asked to understand your ability to manipulate and analyze data using SQL operations such as filtering, aggregating, sorting, and joining tables. So, if you want to…
NumPy, which stands for Numerical Python, is a powerful library in Python providing support for large, multi-dimensional arrays and matrices, along with a vast collection of mathematical functions to operate on these arrays. It serves as a fundamental building block…
Credit scoring and segmentation refer to the process of evaluating the creditworthiness of individuals or businesses and dividing them into distinct groups based on their credit profiles. It aims to assess the likelihood of borrowers repaying their debts and helps…
There are various Data Science tools used in the industry. The usage of different data science tools across companies and professions stems from the diverse nature of their data, objectives, and roles within the industry. Companies, ranging from small startups to large…
The problem of fixing names in a table is a popular SQL question in Data Science interviews. It involves using SQL queries to correct or modify names stored in a particular column. It helps the interviewer understand your data manipulation…
Market basket analysis is a Data Science concept that aims to understand customers’ buying habits to uncover associations and relationships between products. It focuses on analyzing the contents of customers’ shopping carts to identify frequently purchased items together. If you…
Dynamic Pricing is an application of data science that involves adjusting the prices of a product or service based on various factors in real time. It is used by companies to optimize revenue by setting flexible prices that respond to…
Mentioning projects in a resume is of the utmost importance as it allows potential employers to assess your practical skills and abilities. For Data Science jobs, it is essential to mention projects in your resume the right way, as it…
The problem of User Activity Analysis is a popular SQL question in Data Science interviews. It involves extracting and analyzing the user activity data within the designated timeframe of the number of given days. So, if you want to know…
RFM analysis stands for recency, frequency, and monetary value analysis. It is a data science concept used in marketing and customer relationship management. It involves analyzing customer behaviour and segmenting customers based on their transactional history, specifically focusing on three…
Data preprocessing is a critical step in data science tasks, ensuring that raw data is transformed into a clean, organized, and structured format suitable for analysis. A data preprocessing pipeline streamlines this complex process by automating a series of steps, enabling data…
Nike is an American multinational corporation engaged in the design, development, manufacture, marketing and worldwide sale of footwear, apparel, sports equipment, accessories and services. There are many ways how Nike uses Data Science to stay ahead of its competitors worldwide.…
The problem of product sales analysis is a popular SQL question in Data Science interviews. It involves analyzing product sales and identifying top-selling products based on total revenue. So, if you want to know how to solve this problem, this…
ARIMA (autoregressive integrated moving average) is a widely used statistical model for time series analysis and forecasting. It combines three key components: autoregression (AR), differentiation (I), and moving average (MA). In ARIMA models, the p, d, and q values are…
RFM Analysis is used to understand and segment customers based on their buying behaviour. RFM stands for recency, frequency, and monetary value, which are three key metrics that provide information about customer engagement, loyalty, and value to a business. So,…
Customer Segmentation is used to divide a company’s customer base into distinct groups based on common characteristics. It helps companies better understand their customers. If you want to understand Customer Segmentation and how Data Science professionals use this technique, this…
The problem of finding top-performing ads is a popular SQL question in Data Science interviews. It involves analyzing ad performance and identifying top-performing ads based on click-through rate (CTR). So, if you want to know how to solve this problem,…
Python has a remarkably clear and intuitive syntax, which emphasizes readability and thus reduces the burden of program maintenance. It is designed to be easy to understand and implement, making it ideal for beginners as well as Data professionals. So…
In Machine Learning, Scaling and Normalization are techniques used in data preprocessing to transform features or variables in a dataset. These techniques ensure that the data is in an appropriate range and distribution, which facilitates efficient training of Machine Learning…
A hybrid recommendation system is a recommendation technique that offers a complete and balanced approach by mixing two or more recommendation techniques. It aims to provide more accurate, diverse and personalized recommendations to users leveraging the strengths of different techniques…
Exploratory data analysis (EDA) is a Data Science concept where we analyze a dataset to discover patterns, trends, and relationships within the data. If you want to understand Exploratory Data Analysis, this article is for you. In this article, I will…
The problem of deleting duplicate emails is a popular SQL question in Data Science interviews. It involves identifying and removing duplicate records from a table that stores email addresses. So, if you want to know how to solve this problem,…
Exploratory data analysis (EDA) is a Data Science concept where we analyze a dataset to discover patterns, trends, and relationships within the data. It helps us better understand the information contained in the dataset and guides us in making informed…
The currency conversion rate or exchange rate is an important economic indicator affecting several sectors, such as import-export businesses, foreign investment and tourism. By analyzing past data and predicting future exchange rates, we can gain valuable insights to help stakeholders…
Lifetime value analysis calculates the expected value a customer/user will generate over the lifetime of their relationship with the company. So, if you want to know what Lifetime Value Analysis is and how a Data Science professional can help businesses…
The problem of employees earning more than their managers is a popular SQL question asked in Data Science interviews. It involves querying a database to identify employees earning a higher salary than their respective managers. So, if you want to…
H&M is a Sweden-based multinational clothing company that focuses on fast fashion clothing for men, women, teens and children. It is one of GenZ’s favourite brands worldwide. There are many ways in which H&M uses data science to keep its…
In today’s fast-paced e-commerce industry, fast and efficient order delivery is crucial to business success. To ensure seamless order fulfilment, businesses often partner with courier companies to ship their products to customers. However, managing the charges collected by these courier…
Demographic Analysis refers to analyzing data about a population, such as age, gender, income, education, and location, to better understand its characteristics, behaviour, and preferences. So, if you want to know what Demographic Analysis is and how a Data Science…
The problem of Customers Who Never Order is a common SQL question asked in Data Science interviews. It means querying a database to identify customers who have never placed an order. So, if you want to know how to solve…
A Business Analyst is a Data Science professional who uses the data generated by the business to analyze and forecast the performance of a business, design and manage the creation of new data products, and bridge the gap between business stakeholders and…
Loan Approval Prediction is one of the problems that Machine Learning has solved in fintech businesses like banks and financial institutions. Loan approval prediction means using credit history data of the loan applicants and algorithms to build an intelligent system…
Analyzing and Forecasting Time Series is a statistical technique used to analyze data points collected over time. It helps companies identify patterns and trends in the data, which can be used to make informed decisions about the future. So, if…
Finding uncommon words in two sentences is one of the problems in coding interviews. In this problem, you have to find all the words that appear only once in two given sentences. So, if you want to know how to…
In Machine Learning, Polynomial Regression is a regression algorithm used to model nonlinear relationships between input features and output labels. So, if you are new to Machine Learning and want to know how the Polynomial Regression algorithm works, this article…
Stock Market Performance Analysis involves calculating moving averages, measuring volatility, conducting correlation analysis and analyzing various aspects of the stock market to gain a deeper understanding of the factors that affect stock prices and the relationships between the stock prices…
Cohort Analysis is one of the real-time concepts that every Data Science professional should know. Cohort Analysis helps companies analyze and understand the behaviour of their customers or users over time. So, if you want to know what Cohort Analysis…
Transpose Matrix is one of the popular problems in coding interviews. This problem requires you to manipulate a matrix by flipping its rows and columns. So, if you want to know how to transpose a matrix, this article is for…
Support Vector Machine (SVM) is a popular supervised learning algorithm used for classification and regression problems in Machine Learning. The basic idea behind SVM is to find a decision boundary that separates data points of different classes with the maximum…
Customer lifetime value analysis is used to estimate the total value of customers to the business over the lifetime of their relationship. It helps businesses make data-driven decisions on how to allocate their resources and improve their customer relationships. So,…
A/B Testing is one of the real-world concepts you need to know as a Data Science professional. A/B Tests help businesses compare two different options or strategies, such as two different advertisements or website designs, to see which performs better…
Buddy Strings is a popular problem in coding interviews. In this problem, you need to check if it is possible to get two strings, different from exactly a swap of two letters. So, if you want to learn how to…
In Machine Learning, the Random Forest algorithm is an ensemble learning method for classification and regression tasks. It is composed of multiple decision trees, where each tree is built on a random subset of the input features and a random…
Not everyone is always available on social media all the time. Some people limit the use of social media during festive seasons, while some avoid social media during their examinations. So, as Content creators, we need to decide when to…
Content-based filtering and collaborative filtering are two common approaches used in recommendation systems. A Content-based recommendation system uses information about the recommended item, while a collaborative system uses user behaviour data. So, if you want to know how these approaches…
Binary Search is an algorithm used to find an element in a sorted array by repeatedly dividing the search interval in half. In coding interviews, there is always a question on any search algorithm. So, if you want to learn…
In Machine Learning, Decision Tree is an algorithm that works like a flowchart or tree structure to make decisions based on input data. It starts with a question or condition and then follows different branches based on the answers to…
Retail price optimization involves determining the optimal selling price for products or services to maximize revenue and profit. So, if you want to learn how to use machine learning for the retail price optimization task, this article is for you.…
As Data Science beginners, sometimes we need to find datasets to work on projects. And as Data Science professionals, we sometimes need to find synthetic data based on the problem we are working on. So, if you want to know…
Set Mismatch is a popular question in coding interviews. In this problem, you need to find two numbers in an array that are missing or duplicated. So, if you want to know how to solve this problem using Python, this…
In Machine Learning, Naive Bayes is an algorithm that uses probabilities to make predictions. It is used for classification problems, where the goal is to predict the class an input belongs to. So, if you are new to Machine Learning…
Store sales and profit analysis is the task of analyzing the performance of a retail store in terms of its sales and profits. It helps businesses identify areas for improvement and make data-driven decisions to optimize their operations, pricing, marketing,…
Data-driven business models are the types of business models in which data is used for overall business operations. Most big tech product companies you hear about today have data-driven business models. So, if you want to understand what Data-Driven business models…
User Funnel Analysis is a way to analyze the flow of users on a website or an application. It helps analyze the conversion rate on each page visited by the users. So, if you want to know how to analyze…
In Machine Learning, Logistic Regression is a statistical model used for binary classification problems. It is used to predict the probability of an outcome based on the input features. It uses a sigmoid function to map the input features to…
The supply Chain is the network of production and logistics involved in producing and delivering goods to customers. And Supply Chain Analysis means analyzing various components of a Supply Chain to understand how to improve the effectiveness of the Supply…
The first step to getting a job today is to create and upload your resume. The way you used to create a resume some years ago is very different from the way companies want you to. So, if you want…
Reorder routes to make all paths lead to the city zero is a popular question in coding interviews. In this problem, you need to reorder the connections between the cities so that all paths lead to the city labelled as…
In Machine Learning, Linear Regression Algorithm is a statistical technique for calculating the value of a dependent variable based on the value of an independent variable. The goal of linear regression is to find the best-fit line that describes the…
A chatbot is a computer program that understands the intent of your query to answer with a solution. Chatbots are the most popular applications of Natural Language Processing in the industry. So, if you want to build an end-to-end chatbot,…
Myntra is one of the fashion e-commerce platforms in India. It is known for its trending collection of clothing, footwear, and accessories. Myntra uses a lot of Data Science techniques that make it different from other e-commerce platforms. So, if…
Message Encryption means keeping the message secret. In simple words, Message Encryption means putting the message in a secret box that only the receiver can open. If you want to learn how to encrypt messages using Python, this article is…
You must have observed that some applications on your smartphone don’t charge anything but are still profitable. Most companies that are free for a user make money with the data of the users. So, if you want to know how…
Developing Data ETL pipelines is one of the most valuable skills for Data Engineers. Data ETL is a process where data is extracted from a place, then the data is transformed in some way, and then data is loaded into…
The price of a product is one of the most important decisions for every business. It means setting a price for a product or service that is affordable to the target consumer and helps the business remain profitable in the…
The problem of detecting capital is a popular question in coding interviews. A word is written in capital letters if all of its letters are uppercase or if only the first letter is uppercase and the rest are lowercase. In…
Data Preparation is one of the most valuable skills every Data Science professional should have. One challenging task in data preparation is filling in missing values and deciding what measure you should consider between mean, median, and mode to fill…
Accelerometer is a device used to measure the acceleration or vibrations of a motion. The data provided by an accelerometer is three-dimensional and can be used in data-driven applications for solving problems like fall detection and health monitoring. So, if…
Supply Chain Management is the management of the flow of goods from raw materials to the final products and ensuring the delivery of the demanded products at the right place and at the right time. There are many use cases…
The problem of checking perfect numbers is a popular coding interview question. A perfect number is a positive integer equal to the sum of its positive divisors, excluding the number itself. In this problem, you will be given an integer,…
There are many types of questions you are asked for a job interview to understand your behaviour, technical skills, domain expertise, and how you will use your skills in solving real-time business problems. If you are looking for some of…
Employee attrition analysis means analyzing the behaviour of the employees who left your organization and comparing them with the current employees in your organization. It helps in finding which employee may leave soon. So, if you want to learn how…
LinkedIn is a social media platform for working professionals. People use LinkedIn to know about industry trends, job seeking, and growing their professional network. So, if you want to know how LinkedIn uses Data Science, this article is for you.…
The problem of relative ranks is a popular coding interview question. Here you will be given an array of integers representing the scores of athletes, assuming that the athletes with the 1st rank will have the highest score, and you…
Customer Retention means keeping the existing customers loyal towards the business. Retaining customers helps businesses in repeat orders, profitability, and goodwill which attracts more new customers. Today businesses use your data to formulate strategies to retain you as a customer.…
Demand and Supply Analysis is a valuable concept used to analyze the relationship between the quantity demanded and the quantity supplied. If you want to learn about demand and supply analysis and how it helps businesses in the real world,…
Twitter is one of the popular social media applications today. It is known for expressing views in a short piece of text which makes it different from other social media applications. So, if you want to understand how Twitter uses…
The problem of License key formatting is a popular coding interview question. Here you will be given a license key, and you need to reformat the key such that each group contains the same characters except the first group. So,…
Advertising is a marketing strategy that businesses use to promote their products and services. Advertising is not a new concept, it has been used by businesses of all sizes to get more customers over the years. So, if you want…
A recession is an economic situation that arrives when the circulation of money in the economy is low for two consecutive quarters. When the circulation of money is low, it means people are not spending money in the market. When…
Mastercard Inc. is the second largest payment processing corporation worldwide. It offers a range of payment and financial services to businesses and customers worldwide. So, if you want to know how Mastercard uses Data Science for its business, this article…
The problem of constructing a rectangle is a popular coding interview question. Here you will be given the area of a rectangle, and you need to return the height and width of the rectangle to solve this problem. So if…
There is a huge competition in the Data Science field, making it hard to mention unique projects on your resume. An interviewer goes through hundreds of projects every day, so it’s essential to mention unique projects on your resume so…
Topic Modelling means assigning topic labels to a collection of text documents. The goal of topic modelling is to identify topics present in the text documents. So, if you want to learn how to perform topic modelling, this article is…
Samsung is a South Korean multinomial conglomerate. It is known for its midrange and flagship smartphone collection worldwide. There are many ways how Samsung uses Data Science and Machine Learning techniques in its technology and business. So, if you want…
The problem of max consecutive ones is a popular coding interview question. Here you will be given a binary array, and you need to return the maximum number of consecutive 1s in the array. So, if you want to know…
Your LinkedIn profile is like an online resume. Today, companies do have a look at your LinkedIn profile before hiring you, especially in the tech industry. So, if you want to know how to create a LinkedIn profile to get…
Text emotions classification is the problem of assigning emotion to a text by understanding the context and the emotion behind the text. One real-world example is the keyboard of an iPhone that recommends the most relevant emoji by understanding the…
There have been many innovations in the healthcare industry since the outbreak of covid in 2019. The use of data in the healthcare industry has helped healthcare professionals get more accurate information about the medical conditions of patients. In this…
The problem of hamming distance between two integers is a popular coding interview question. Here you will be given two integers, and you need to calculate the number of positions at which the corresponding bits of the integers are different. So, if…
A Data Engineer is a data professional who collects, transforms, and process data according to the need of the business. Data Engineering is one of the highest-paying jobs in Data Science. So, if you are looking for a roadmap to…
App user segmentation is the task of grouping users based on how they engage with the app. It helps find retained users, find the user segment for a marketing campaign, and solve many other business problems where you need to…
The problem of the Repeated Substring Pattern is a popular coding interview question. Here you will be given a string, and you need to check if the given string can be formed by repeating a substring of the string. So,…
Data Analysis means analyzing data to gather valuable insights that can be used in decision-making and solving various business problems. The role of a Data Analyst is one of the best jobs to start your journey as a Data Science…
Algorithmic Trading is the use of algorithms in the financial market to make trading decisions. JP Morgan Chase & Co. is one of the businesses that use Algorithmic Trading for investment decisions. So, if you want to learn how to…
Tata Consultancy Services is an Indian multinational corporation that provides IT, data processing and consulting services. TCS is one of the highly active recruiters in India for its IT and data processing services. So, if you want to know how…
The problem of assigning cookies is a popular coding interview question. Here you will be given a list of children with their greed factors and a list of cookies with their sizes. To solve this problem, you need to assign…
The decision Tree algorithm is a supervised Machine Learning algorithm used for both classification and regression problems. It is based on a sequential decision process. If you want to know everything about the Decision Tree algorithm, this article is for…
Ads Click Through Rate is the ratio of how many users clicked on your ad to how many users viewed your ad. For example, 5 out of 100 users click on the ad while watching a youtube video. So, in…
Dream11 is a fantasy sports platform where you can create a virtual team of real sports players and participate in fantasy games. Dream11 has many use cases of Data Science that make it different from all other fantasy gaming applications.…
Calculating the distance between two locations helps companies like Swiggy and Zomato calculate the delivery time for an order. If you want to learn how to calculate the distance between two locations by using their latitude and longitude points, this…
A box plot is a data visualization technique for analyzing the distribution and patterns of numerical data points. Understanding data visualization graphs is not easy for everyone. So if you want to know how to analyze a box plot, this…
A career aspirations survey gathers information about the goals and aspirations of people in their careers. It includes questions based on long-term goals, preferred work environment, interests, and values. So, if you want to learn how to analyze the information…
JP Morgan Chase & Co. is an American multinational investment banking and financial services company. Like other successful financial services businesses, Data Science is one of the reasons behind the success of JP Morgan Chase. So, if you want to…
The problem of counting the number of segments in a string is a popular coding interview question. Here you will be given a string, and you have to count the number of non-space characters in the string. So, if you…
A scatter plot is a data visualization technique to analyze relationships between two variables and find outliers. Understanding data visualization graphs is not easy for everyone. So if you want to know how to analyze a scatter plot, this article…
Food Delivery services like Zomato and Swiggy need to show the accurate time it will take to deliver your order to keep transparency with their customers. These companies use Machine Learning algorithms to predict the food delivery time based on…
Zomato is an Indian restaurant aggregator and food delivery company. It is known for faster delivery of food from anywhere in your city. Like every successful business today, Data Science is one of the reasons behind the success of Zomato.…
The problem of finding the third maximum number is a popular coding interview question. Here you will be given an array, and you have to return the third largest number in the array as an output. So, if you want…
Getting a Data Science job is hard for freshers without any work experience. So what should you do as a fresher? As a fresher, you can focus on entry-level job roles in Data Science to get experience. In this article,…
The Social Progress Index (SPI) is a measure that gives an understanding of social progress globally. It helps in understanding how much countries care about the overall development of the citizens. If you want to know how to analyze the…
Nykaa is one of the popular e-commerce platforms in India. It is known for beauty, wellness, and fashion products. Like every successful business today, Data Science is one of the reasons behind the success of Nykaa. So, if you want…
The FizzBuzz problem is a popular coding interview question. Here you need to check if a number is divisible by 3 and 5 and return the output based on some conditions. If you want to know how to solve the…
As a Data Science beginner, you need to work on various projects to get your desired job. Working on projects is valuable because your projects are the highlights of your resume when you are a fresher. Once you get experienced,…
Recommendation Systems are one of the popular applications of Data Science for every e-commerce platform. When it comes to fashion, an e-commerce platform wants to recommend the most trending fashion to its users for higher sales and engagement. Myntra is…
Spotify is an audio streaming platform with over 456 million monthly active users. Spotify is one of the best examples of companies that use Data Science and Machine Learning techniques to provide its services. So, if you want to know…
The problem of finding the first unique character in a string is a popular coding interview question. Here you will be given a string, and you have to return the index of the first non-repeating character in the string as…
One of the reasons behind the success of many businesses is how they use the data generated by their business and customers in decision-making and improving their products and services. So, if you want to know how companies worldwide use…
A recommendation system is a popular application of Data Science that recommends personalized content based on the users’ interests. Almost all the popular websites you visit today use a recommendation system. As the name suggests, a job recommendation system is…
Paytm is a digital payments and financial services company. Just like other fintech companies, data is the ABC for Paytm. So, if you want to know how Paytm uses Data Science, this article is for you. In this article, I…
Validating perfect squares is a popular coding interview question. Here you will be given an integer, and you have to check if the integer is a perfect square. So, if you want to learn how to validate perfect squares, this…
In Machine Learning, we use data and algorithms to build intelligent systems. In the next ten years, you will explore many new high-paying jobs that require you to know about Machine Learning. So the time you will spend today learning…
Banks and credit card companies calculate your credit score to determine your creditworthiness. It helps banks and credit card companies immediately to issue loans to customers with good creditworthiness. Today banks and credit card companies use Machine Learning algorithms to…
Youtube is a popular social media platform where we can upload videos to educate or entertain an audience of every kind. There are many areas where Youtube uses Data Science for its business and to provide a better user experience.…
Counting Bits is a popular coding interview question. Here you will be given an integer, and you have to return an array of length (length of the integer + 1) by counting the number of 1’s in the binary representation…
Data Science is one of the highest-paying career options today. There are many jobs in the Data Science field you can prepare for as a fresher or an experienced professional. So, if you want to know about the highest-paying career…
Consumer Complaint Classification means classifying the nature of the complaint reported by the consumer. It is helpful for consumer care departments as they receive thousands of complaints daily, so classifying them helps identify complaints that need to be solved first…
Apple is one of the most loved tech brands worldwide. Most of the products of Apple are known for productivity, user experience, and privacy. There are many ways how Apple is using Data Science and Machine Learning in its products…
The problem of the power of three is a popular coding interview question. Here we need to check whether the input value is the power of three or not. So, if you want to know how to solve this problem…
A Business Analyst is a Data Science professional who analyzes and forecasts business trends, understands and analyzes business strategies, and performs budgeting and financial analysis of the business. If you are aiming for the role of a Business Analyst and…
Every sports event generates a lot of data which we can use to analyze the performance of players, teams, and many highlights of the game. As the ICC Men’s T20 world cup has just finished, it has generated a lot…
Netflix is a subscription-based streaming platform that allows users to watch movies and TV shows without advertisements. One of the reasons behind the popularity of Netflix is the way Data Science is used at Netflix to improve its services as…
Moving zeroes is one of the popular questions in coding interviews. Here we need to move all the 0’s in an array to the end of the array while keeping the order of non-zero elements the same. So, if you…
Data Science is one of the highest-paying career options today. But many freshers find it hard to get their first Data Science job. Companies need experience, freshers look for work to become experienced, and the loop continues. So how to…
A/B Testing means analyzing two marketing strategies to choose the best marketing strategy that can convert more traffic into sales (or more traffic into your desired goal) effectively and efficiently. A/B testing is one of the valuable concepts that every…
Like all other jobs, the salary of a Machine Learning Engineer depends on many factors like work experience, living standards in the country, and demand for Machine Learning Engineers in the country. Out of all factors, work experience is the most important…
Grammarly is one of the best examples of applications that use Machine Learning for their business. Grammarly helps write a text for any purpose and uses Machine Learning to make that text more readable and engaging. So, if you want…
Ugly numbers are the numbers whose prime factors are limited to 2, 3, and 5. Finding the Ugly number is a popular question in coding interviews. Here you need to check if a number is an ugly number or not.…
Data Science is one of the highest-paying career options today. Data Science is not like Engineering, where you need an engineering degree with a computer science background. Data Science is a skill that helps companies make decisions with data. So…
Twitter is one of the popular social media applications where people share what they feel in a limited number of words. Twitter is popular but not in the stock market. As Twitter is being delisted from the New York stock…
Like all other jobs, the salary of a Data Scientist also depends on many factors like work experience, living standards in the country, and the demand for Data Science professionals in the country. Out of all these factors, work experience…
Instagram is one of the most popular social media applications today. Just like every business today, there are many areas where Instagram uses Data Science. So, if you want to know how Instagram uses Data Science, this article is for…
The problem of adding digits is a popular coding interview question. Here we need to add all the digits of the integer till we get to a single-digit integer. So, if you want to know how to solve this problem using…
Data Science is one of the highest-paying career options today. There are many free and paid platforms today where you can learn everything about Data Science. So, if you are looking for the platforms you should follow to learn Data…
Salary differs according to the job profile of the person. But generally, it’s the working experience that determines the salary. Salary prediction is a popular problem among the Data Science community for complete beginners. So, if you are a beginner…
With the increase in competition in the computer science field, coding interviews are getting tougher. It is now hard for freshers to get their first job in their dream companies. Although there are many free resources on the internet, if you are…
Google is the most used search engine worldwide. One of the reasons behind the success of Google as a search engine is the way Google uses Data Science to improve its search results for every user. So, if you want…
The problem of Power of Two is a popular coding interview question. Here we need to check whether the input value is the power of two or not. So, if you want to know how to solve this problem using Python, this…
Screen Time Analysis lets you know how much time you spend on what kind of applications and websites using your device. And screen time analysis gives a visual report of the same. So, if you want to learn how to…
A time series data is a sequence of data collected over an interval of time. When we work on time series data to analyze and find patterns, it is known as Time Series Analysis and forecasting. So, if you are looking for…
Amazon is one of the largest e-commerce platforms today. One of the reasons behind the success of Amazon is the way Amazon uses Data Science for its business. So, if you want to know how Amazon uses Data Science, this article is for…
The duplicate values problem is a popular coding interview question. Here we need to check if any value appears at least twice in an array. So, if you want to know how to solve this problem using Python, this article…
Data Scientists and Data Analysts are Data Science professionals with some skills in common and different responsibilities. So, if you don’t know how a Data Scientist differs from a Data Analyst, this article is for you. In this article, I…
In Data Science, weather forecasting is an application of Time Series Forecasting where we use time-series data and algorithms to make forecasts for a given time. If you want to learn how to forecast the weather using your Data Science…
Kaggle is a Data Science community owned by Google. You will find thousands of datasets and case studies on Kaggle to improve your Data Science skills. So, if you are looking for some case studies to practice your Data Science…
Tinder is an online dating and geosocial platform. Many users find Tinder helpful for meeting new people for friendships and relationships. Just like every business today, Tinder also use Data Science for its business. So, if you want to know how Tinder uses…
The majority element problem is one of the popular coding interview questions. Here we need to find the element that appears more than the other element in an array. So, if you want to know how to solve this problem,…
Data Scientists and Data Engineers are Data Science professionals with some skills in common and different responsibilities. If you don’t know how a Data Scientist differs from a Data Engineer, this article is for you. In this article, I will…
Flipkart introduces a sale every year during the festive season in India. This sale is known as the Big Billion Days sale. The focus of the sale is on electronics of every kind, including flagship smartphones. So, if you want…
There are many tools Data Science professionals use daily to solve business problems with data. To become a Data Science professional, you need to learn all the necessary tools. So, if you want to know about the tools and software…
Uber is an American mobility-as-a-service provider that currently operates in 72 countries. Uber is also among the companies that use data and algorithms as a necessity for their business. So, if you want to know how Uber uses Data Science, this…
The excel sheet column title is one of the popular coding interview questions. Here we need to return the corresponding column title of an integer as displayed in an excel sheet. So, if you want to know how to solve…
Data Scientists and Machine Learning Engineers are Data Science professionals with different skillset and responsibilities. So, if you are confused about how a Data Scientist differs from a Machine Learning Engineer, this article is for you. In this article, I…
Credit card clustering is the task of grouping credit card holders based on their buying habits, credit limits, and many other financial factors. If you want to learn how to use clustering analysis to group credit card holders, this article…
In Machine Learning, we use data and algorithms to build intelligent systems. If you are preparing for a job based on Machine Learning and confused about what kind of projects you should work on to mention in your resume, this…
In Machine Learning, we use data and algorithms to build intelligent systems. It doesn’t matter if you want to become a Machine Learning Engineer, Data Scientist, or Data Analyst. If you want any job in the Data Science field, you need…
The Single Number problem is one of the popular coding interview questions. Here you will be given an array of integers where each item appears twice except for one that we need to find. So, if you want to know how…
Regression analysis is a machine learning technique used to predict continuous values. Once you have trained a regression model to predict Continuous values based on the problem you are solving, it is valuable to evaluate the model’s performance. So, if…
A diamond is one of the most expensive stones. The price of diamonds varies irrespective of the size because of the factors affecting the price of a diamond. So, if you want to learn how to use your Data Science…
Python is one of the most popular programming languages today. The popularity and beginner-friendly nature of Python’s syntax have made it accepted in almost every domain worldwide. To get your first job as a Python developer, you need to work…
Python is one of the most popular programming languages today. It is preferred by Data Science professionals and Web Developers worldwide. There are a lot of free and paid courses on the internet to learn Python. So, if you are…
Palindrome words are words that are read the same backward as forward. For example, mom, dad, and madam are palindrome words. Validating palindrome words is one of the popular coding interview questions. So, if you want to learn how to…
Data Science is the combination of data mining and computer science. As the use of data has increased in every domain, Data Science is one of the highest-paying career options today. If you want to learn Data Science and looking…
Apple iPhones are among the top-selling smartphones worldwide. There is huge competition among smartphone brands in India, where you can get the latest technology in a smartphone at half the price of an iPhone. Still, there are high sales of iPhones…
Instagram is one of the most popular social media apps today. It contains valuable features for both content creators and consumers. There are many areas where Instagram uses Data Science to make it more helpful to its users. So, if…
Data Science is one of the highest-paid career options today. If you want to learn Data Science, you don’t need to spend a lot as there are so many free resources on the internet to learn Data Science. So, if…
Finding the best time to buy and sell stocks is one of the popular coding interview questions. Here we need to return the maximum profit we can achieve from buying and selling a stock. So, if you want to learn…
A recommendation system is a popular application of Data Science. Almost all the popular websites you visit use recommendation systems. As the name suggests, a news recommendation system is an application that recommends news articles based on the news a user is…
Business Forecasting is one of the popular applications of Data Science. In Business Forecasting, we use the data generated by the business to forecast the future sales, expenditure, or revenue of the company. If you are looking for some project…