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…
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…
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.…
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…
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…
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…
The rent of a house depends on a lot of factors. With appropriate data and Machine Learning techniques, many real estate platforms find the housing options according to the customer’s budget. So, if you want to learn how to use…
Time Series Forecasting means analyzing and modeling time-series data to make future decisions. Some of the applications of Time Series Forecasting are weather forecasting, sales forecasting, business forecasting, stock price forecasting, etc. The ARIMA model is a popular statistical technique…
Student marks prediction is a popular data science case study based on the problem of regression. It is a good regression problem for data science beginners as it is easy to solve and understand. So if you want to learn…
Covid-19 is one of the deadliest viruses you’ve ever heard. Mutations in covid-19 make it either more deadly or more infectious. We have seen a lot of deaths from covid-19 while there is a higher wave of cases. We can…
Instagram is one of the most popular social media applications today. People using Instagram professionally are using it for promoting their business, building a portfolio, blogging, and creating various kinds of content. As Instagram is a popular application used by…
Predicting the future sales of a product helps a business manage the manufacturing and advertising cost of the product. There are many more benefits of predicting the future sales of a product. So if you want to learn to predict…
Netflix is one of the most popular OTT streaming platforms. It offers a vast collection of television series and films and owns its productions known as Netflix Originals. People who are highly active in stock market investments always keep an…
Tipping waiters for serving food depends on many factors like the type of restaurant, how many people you are with, how much amount you pay as your bill, etc. Waiter Tips analysis is one of the popular data science case…
You must have heard or invested in any cryptocurrency once in your life. It is a digital medium of exchange that is encrypted and decentralized. Many people use cryptocurrencies as a form of investing because it gives great returns even…
In Data Science, Time Series data is a sequence of data points collected and indexed according to time. When we analyze such kinds of data to find patterns over an interval of time, it is known as Time Series Analysis.…
In Data Science, Time Series Analysis is a method of analyzing data collected over an interval of time. Stock price data and covid-19 cases data are examples of time-series data. Time Series Analysis helps understand the underlying causes of trends…
You must have studied that the demand for a product varies with the change in its price. If you take real-world examples, you will see if the product is not a necessity, then its demand decreases with the increase in…
The price of electricity depends on many factors. Predicting the price of electricity helps many businesses understand how much electricity they have to pay each year. The Electricity Price Prediction task is based on a case study where you need…
Health Insurance is a type of insurance that covers medical expenses. A person who has taken a health insurance policy gets health insurance cover by paying a particular premium amount. There are a lot of factors that determine the premium…
Recently, we have seen an increase of more than 10 per cent in the stock price of Tata Motors. This has resulted in more attention to Tata Group stocks from all over India. But again today, we are witnessing a…
Predicting the number of orders for a product is one of the strategies a business can follow in determining how much to invest in marketing their product. So, predicting the number of orders is an important data science use case…
Apple has just announced the date of its September event when it is about to launch the new iPhone 13. It is currently the center of attention on the stock market. Stock market analysis is one of the popular applications…
There are so many social media platforms today where you will find so many content creators in so many types of fields. As a social media consumer, the number of followers you have may not be of interest to you,…
The price of a car depends on a lot of factors like the goodwill of the brand of the car, features of the car, horsepower and the mileage it gives and many more. Car price prediction is one of the…
In Data Science, when we are working on a problem whose output depends on periods or intervals, it means that we are working on a problem based on a time series analysis. If you want to work on some data…
Passive Aggressive Regression belongs to the category of online learning in machine learning. It is not one of the most commonly used machine learning algorithms, but it can nonetheless be used to achieve efficient results that solve regression-based problems. So,…
Microsoft is today one of the largest technology companies with more than 163,000 employees worldwide. It is known for the Windows operating system which is one of the most popular computer operating systems. If you want to learn how to…
Video game sales analysis is a popular problem statement on Kaggle. You can work on this problem to analyze the sales of more than 16,500 games or you can also train a machine learning model for forecasting video game sales.…
Regression is a machine learning technique used in finance, investing, and other related fields to determine the relationship between a dependent variable and a series of independent variables. Simply put, when we want to predict the future values of a…
Dogecoin is the reason for the recent drop in bitcoin prices. The price of Dogecoin is currently very cheap compared to bitcoin, but some financial experts, including Tesla’s CEO Elon Musk, claiming that we will see a rise in the…
Currency exchange is one of the biggest financial markets. Currently, 1 United States dollar is equivalent to 73.02 Indian rupees. Many factors affect exchange rates such as economic, political and even psychological factors. The prediction of the currency exchange rate…
Forecasting sales is a difficult problem for every type of business, but it helps determine where a business should spend more on advertising and where it should cut spending. In this article, I will walk you through the task of…
Polynomial regression is a machine learning algorithm that is used to train a linear model on non-linear data. Sometimes your data is much more complex than a straight line, in such cases, it is not a good option to train…
A company should always set a goal that should be achievable, otherwise, employees will not be able to work to their best potential if they find that the goal set by the company is unachievable. The task of profit prediction…
In graduate studies, many students find it difficult to achieve good grades because they do not get much support in higher education courses compared to the support that students receive in schools. We can use machine learning for the student…
Tesla is an amAmericanlectric vehicle company whose aim is to accelerate the world’s transition towards sustainable energy. A few days back the rise in the stock prices of Tesla made Elon Musk the richest person in the world. Predicting stock…
Linear and logistic regression are excellent statistical techniques used as machine learning algorithms to understand the relationship between features and labels in machine learning. In this article, I will take you through the difference between linear regression and logistic regression…
In this article, I am going to walk you through how we can train a model that will help us predict car prices with Machine Learning using PyTorch. The dataset I’m going to use here to predict car prices is…
In this article, I will use the algorithm provided by Facebook, popularly known as Facebook Prophet Model. I will use the Facebook Prophet Model for Daily Births Forecasting using Machine Learning. The Data I will use here is a very…
PyTorch is a Python library that facilitates the creation of deep learning models. PyTorch is very flexible and easy to use for deep learning tasks. The accessibility and friendliness of early adopters in the years that followed its first publication,…
Stock Price Prediction means to determine the future value of the stocks or other financial instruments of an organisation. If you master the art to predict stock prices, you can earn a lot by investing and selling at the right…
In this Article I will create a Linear Regression model and a Decision Tree Regression Model to Predict Google Stock Price using Machine Learning and Python. Download the data set Import pandas to import a CSV file: To get the…