Data Science | Machine Learning | Python
Fraud is one of the major issues we come up majorly in banks, life insurance, health insurance, and many others. These major frauds are dependent on the person who is trying to sell you the fake product or service, if you are matured enough to decide what is wrong then you will never get into […]
The Random Forest algorithm is an ensemble of the Decision Trees algorithm. A Decision Tree model is generally trained using the Bagging Classifier. If you don’t want to use a bagging classifier algorithm to pass it through the Decision Tree Classification model, you can use a Random Forest algorithm as it is more convenient and […]
Have you ever faced problems in getting started with Data Science and Machine Learning? If you are doing a course from a very respective university still you face problems with lack of concepts and knowledge of the basics. So you must have tried to find mentors around yourself. Luckily, we have so many mentors around […]
Indeed, two people can never have the same fingerprints, it is unique in every human. But using fingerprints we can classify gender, whether it’s male or female. In this article, I will take you through a Gender Classification Model which I will train using Deep Learning and Convolutional Neural Networks. Now you must be thinking […]
In this article, I will show you, 5 Beginner, to Intermediate level Artificial Intelligence Projects. Artificial Intelligence consists of three main components, which are Data Science, Machine Learning, and Deep Learning. All the projects are solved and explained. If you are new to Artificial Intelligence and Machine Learning and want to improve yourself more before […]
Machine Learning and Artificial Intelligence are the most searched content on the Internet among the programmers coming from different programming languages. The popularity of Machine Learning has led to a lot of research that today we have even reached to the concept of AutoML, where we can automate machine learning tasks by automating some of […]
In this article, I will show you 5 beginner level Machine Learning Projects for Beginners. All the projects are solved and explained. If you are new to Machine Learning and want to improve yourself more before getting into projects you can go through my free course here. If you have already gone through some valuable […]
In Machine Learning, one way to use the same training algorithm for more prediction models and to train them on different sets of the data is known as Bagging and Pasting. Bagging means to perform sampling with replacement and when the process of bagging is done without replacement then this is known as Pasting. Why […]
A dictionary is an example of a key-value store also known as Mapping in Python. It allows you to store and retrieve elements by referencing a key. As dictionaries are referenced by key, they have very fast lookups. As they are primarily used for referencing items by key, they are not sorted. Creating a Dictionary […]
Suppose you are planning to buy a new car. Your planning is never going to be as short as moving to the showroom and coming back home in a car. You will probably plan a lot even before seeing your first option. Now, you have selected 5 cars in your list, now you are confused […]
Suppose you have trained a lot of classification models, and your each model is achieving the accuracy of 85 percent. A very simple way to create an even better classifier is to aggregate the predictions of each classifier and predict the class that gets the most votes. This majority-vote classification is known as a voting […]
As one of the most basic functions in programming, loops are an important piece to nearly every programming language. Loops enable developers to set certain portions of their code to repeat through several loops, referred to as iterations. This topic covers using multiple types of loops and applications of loops in Python. For loops for […]
You must have seen many articles and tutorials on web scraping. Even I have written an article on it. In this article, I will do something different, that is scraping Instagram with Python. It is an easy task until you get errors in writing your usernames and passwords. Here I will show you some techniques […]
The general goal of a classification model is to find a decision boundary. The purpose of the decision boundaries is to identify those regions of the input class space that corresponds to each class. In this article, I will take you through the concept of decision boundary in machine learning. To explain the concept of […]
Data types are variables that are used to store values. In Python, variables do not need a pre declaration; the declaration of variables in Python happens automatically when we assign any value to a variable. Just like variables, data types in Python also do not need any declaration. They will be declared automatically whenever we […]
Anomaly Detection means detecting unexpected events in the dataset which differ from the norm. Anomaly Detection is very often used in unlabeled data. There are two most important assumptions in the task of Anomaly Detection: the first assumption says that Anomalies occurs very rarely in data, and the second assumption is that the features differ […]
The Ridge Regression is a regularized version of a Linear Regression. The Ridge Regression enables the machine learning algorithms to not only fit the data but also to keep weights of the model as small as possible. It is quite familiar with the cost function that is used while training to be different from the […]
Machine Translation is one of the most challenging tasks in Artificial Intelligence that works by investigating the use of software to translate a text or speech from one language to another. In this article, I will take you through Machine Translation using Neural networks. At the end of this article, you will learn to develop […]
Audio Feature Extraction has been one of the significant focus of Machine Learning over the years. The most frequent common state of data is a text where we can perform feature extraction quite smoothly. Then we have Feature Extraction for the image, which is a challenging task. Now I will show you Audio Feature Extraction, […]
What will you do if your data is a bit more complicated than a straight line? A good alternative for you is that you can use a linear model to fit in a nonlinear data. You can use the add powers of ever feature as the new features, and then you can use the new […]
Gradient Descent is an optimisation algorithm which is capable of providing optimal performance to a wide range of tasks in Machine Learning. The idea behind a Gradient Descent algorithm is to tweak the parameters using loops to minimize the cost function. In this article, I will take you through the Gradient Descent algorithm in Machine […]
The Receiver Operating Characteristic (ROC) curve is a popular tool used with binary classifiers. It is very similar to the precision/recall curve. Still, instead of plotting precision versus recall, the ROC curve plots the true positive rate (another name for recall) against the false positive rate (FPR). The FPR is the ratio of negative instances […]
In Machine Learning, Precision and Recall are the two most important metrics for Model Evaluation. Precision represents the percentage of the results of your model, which are relevant to your model. The recall represents the percentage total of total pertinent results classified correctly by your machine learning algorithm. In this article, I will show you […]
Testing and Validation are the only way to know how well a model will generalize to new cases is to actually try it out on new cases. One way to do that is to put your model in production and monitor how well it performs. This works well, but if your model is horribly bad, […]
OpenAI Gym is a toolkit that provides a wide variety of simulated environments (Atari games, board games, 2D and 3D physical simulations, and so on), so you can train agents, compare them, or develop new Machine Learning algorithms (Reinforcement Learning). OpenAI is an artificial intelligence research company, funded in part by Elon Musk. Its stated […]
Image filtering is used to enhance the edges in images and reduce the noisiness of an image. This technology is used in almost all smartphones. Although improving an image using the image filtering techniques can help in the process of object detection, face recognition and all tasks involved in computer vision. In this article, I […]
Data Visualisation plays a major role to study and analyse data to extract useful insights that can add value to our end task. Python being a universal language provides a lot of libraries for almost every task you have ever heard of. The most common libraries for data visualization in Python are Matplotlib and Plotly. […]
In this article I will take you through a Trading Strategy with Machine Learning, which can be used to determine when you should buy stocks and when you should sell. Generally it is not easy to predict stock market, but building a Trading Strategy using Machine Learning can make it easy. Trading Strategy with Machine […]
There are so many different types of Machine Learning systems that it is useful to classify them in broad categories, based on the following criteria: Whether or not they are trained with human supervision (supervised, unsupervised, semisupervised, and Reinforcement Learning) Whether or not they can learn incrementally on the fly (online versus batch learning) Whether […]
I recently shared an article on Audio Processing with Python. It was about how you can process and manipulate an audio file with Python. If you have gone through that, now you must know about how the basic stuff of audio data is handled with programming. In this article, I will take you through the […]
In this article, I will take you through a brief explanation of Image Segmentation in Deep Learning. I will only explain the concept behind the image segmentation here in this article. If you want to go through the practical part of Image Segmentation you can see it’s tutorial here. Image Segmentation in Deep Learning In Image […]
Machine Learning is a Very Broad Field. If Machine Learning is a dish, then linear algebra, programming, analytical skills, statistics, and Algorithms are the primary recipes of Machine Learning. If you will go more deep inside the Machine Learning concepts, you will get confused about what to learn first or what to not focus much. […]
If you are using Scikit-Learn, you can easily use a lot of algorithms that are already made by some famous Researchers, Data Scientists, and other Machine Learning experts. Have you ever thought of building your algorithm instead of using a module like Scikit-Learn? All the Machine Learning Algorithms that Scikit-Learn provides are easy to use […]
Sometimes, while doing programming, we need to go through some audio processing stuff. Some of the most used audio processing tasks in programming include – loading and saving audio files, splitting and appending the audio files into segments, creating mix audio files using different data, manipulating the levels of sound, applying some filters, and generating […]
Have you ever thought how Snapchat manage to apply amazing filters according to your face? It have been programmed to detect some marks on your face to project a filter according to those marks. In Machine Learning those marks are known as Face Landmarks. In this article I will guide you how you can detect […]
Being a practitioner in Machine Learning, you must have gone through an image classification, where the goal is to assign a label or a class to the input image. Now, suppose you want to get where the object is present inside the image, the shape of the object, or what pixel represents what object. In […]
Machine Learning Pipelines performs a complete workflow with an ordered sequence of the process involved in a Machine Learning task. In most of the functions in Machine Learning, the data that you work with is barely in a format for training the model with it’s the best performance. There are several steps in the process […]
TensorBoard is a great interactive visualization tool that you can use to view the learning curves during training, compare learning curves between multiple runs, visualize the computation graphs, analyze training statistics, view images generated by your model, visualize complex multidimensional data automatically when you install TensorFlow, so you already have it. Getting Started with TensorBoard […]
Where Binary Classification distinguish between two classes, Multiclass Classification or Multinomial Classification can distinguish between more than two classes. Some algorithms such as SGD classifiers, Random Forest Classifiers, and Naive Bayes classification are capable of handling multiple classes natively. Others such as Logistic Regression or Support Vector Machine Classifiers are strictly binary classifiers. However, there […]
Most of the keyboards in smartphones give next word prediction features; google also uses next word prediction based on our browsing history. So a preloaded data is also stored in the keyboard function of our smartphones to predict the next word correctly. In this article, I will train a Deep Learning model for next word […]
Data Augmentation is a technique in Deep Learning which helps in adding value to our base dataset by adding the gathered information from various sources to improve the quality of data of an organisation. Data Augmentation is one of the most important processes that makes the data very much informational. Improving the data is very […]
Binary Classification is a type of classification model that have two label of classes. For example an email spam detection model contains two label of classes as spam or not spam. Most of the times the tasks of binary classification includes one label in a normal state, and another label in an abnormal state. In […]
You must have seen a cloud filled with words in a lot of Analysis tasks and machine learning projects. A WordCloud represents the importance of each word in a set of words by analyzing the frequency of terms. In this article, I will take you through a detailed understanding of a WordCloud. At the end […]
In this article you will learn to create databases, manipulate databases, and will also learn some operations on handling databases in MySQL with Python. You need to download and install MySQL from here, and after installing MySQL you also need to server to use it with Python. mysql.connector will provide you the features as a […]
Birds inspired us to fly, nature inspired us to countless inventions. It seems logical, then to look at the brain’s architecture for inspiration on how to build an Intelligent Machine. This is the logic that sparked Artificial Neural Networks (ANN). ANN is a Machine Learning Model inspired by the networks of biological neurons found in […]
Fake News is one of the major concerns in our society right now. It is a very widespread issue that even the most leading media sometimes gets with the trap of Fake News. If it’s difficult for media channels to detect fake news then it’s next to difficult for a general citizen. As a part […]
There are two main approaches to training models across multiple devices; model parallelism, where the model is split across the devices, and data parallelism, where the model is replicated across every device, and each replica is trained on a subset of the data. Let’s look at these two options closely to understand how training models […]
In this article I will show you how you can create your own dataset by Web Scraping using Python. Web Scraping means to extract a set of data from web. If you are a programmer, a Data Scientist, Engineer or anyone who works by manipulating the data, the skills of Web Scrapping will help you […]
An AI Chatbot is one of the most achieved goals in the field of Artificial Intelligence. Today Chatbot can help you in every way from assisting you to order something online to guide you through a Business Plan. Every Brand is having an AI Chatbot for their purposes. In this article, I will show you […]
In this article, I will take you through a very powerful algorithm in Machine Learning, which is the Grid Search Algorithm. It is mostly used in hyperparameters tuning and models selection in Machine Learning. Here I will teach you how to implement this algorithm using python. At the end of this article, you will learn […]
In this article, we will look at how to speed up your models by using a GPU. We will also see how to split the computations across multiple devices, including the CPU and numerous GPU devices. Thanks to GPUs, instead of waiting for days or weeks for a training algorithm to complete, you may end […]
Natural Language Processing or NLP is a field of Artificial Intelligence which focuses on enabling the systems for understanding and processing the human languages. In this article, I will use NLP to analyze my WhatsApp Chats. For some privacy reasons, I will use Person 1, Person 2 and so on in my WhatsApp Chats. Get […]
PyTorch is a library in Python which provides tools to build deep learning models. What python does for programming PyTorch does for deep learning. Python is a very flexible language for programming and just like python, the PyTorch library provides flexible tools for deep learning. If you are learning deep learning or looking to start […]
In Data Science, you must have seen people reading CSV files and excel files to work with the data, but what about a PDF. Python is a very high level language that is the reason it is mostly getting used in Machine Learning and Artificial Intelligence. So using Python for PDF is probably as easy […]
Machine Learning has been an outstanding achievement in the field of Artificial Intelligence. The algorithms behind the success of Machine Learning are Deep Neural Networks which were made after research of years through the expert researchers. The only difficulties the researchers faced was the discovery of AutoMl. AutoML is that field that aims to automate […]
If you want to deploy your TensorFlow model to a mobile or embedded device, a large model may take too long to download and use too much RAM and CPU, all of which will make your app unresponsive, heat the device and drain its battery. To avoid this, you need to make a mobile-friendly. Lightweight, […]
I have trained and developed a lot of Machine Learning models, if you are a student in Machine Learning, you must have also developed models. In this article, I will train and Deploy a Machine Learning Model using Flask step by step. I will first train a model, then I will work to serve our […]
In Economics, Price Elasticity of Demand (PED) is used to measure the responsiveness or elasticity of the quantity demanded of a product or service due to the increase or decrease in the price of the product. In simple terms Price Elasticity of Demand gives the percentage change in the quantity demanded of a product due […]
PySpark is the API of Python to support the framework of Apache Spark. Apache Spark is the component of Hadoop Ecosystem, which is now getting very popular with the big data frameworks. Apache Spark is a very powerful component which provides real time stream processing, interactive frameworks, graphs processing, batch processing and in-memory processing in […]
According to the report of Centers of Disease Control and Prevention about one in seven adults in the United States have Diabetes. But by next few years this rate can move higher. With this in mind today, In this article, I will show you how you can use machine learning to Predict Diabetes using Python. […]
Many clustering algorithms are available in Scikit-Learn and elsewhere, but perhaps the simplest to understand is an algorithm known as k-means clustering, which is implemented in sklearn.cluster.KMeans. Introduction The k-means algorithm searches for a pre-determined number of clusters within an unlabeled multidimensional dataset. It accomplishes this using a simple conception of what the optimal clustering looks […]
This article features the implementation of an employee turnover analysis that is built using Python’s Scikit-Learn library. In this article, I will use Logistic Regression and Random Forest Machine Learning algorithms. At the end of this article, you would be able to choose the best algorithm for your future projects like Employee Turnover Prediction. What […]
If you want to find out who are your best customers, using an old technique RFM matrix principle is still the best in the business. RFM means – Recency, Frequency and Monetary. RFM is basically a customer segmentation technique that works by using the past behaviour of your customers based on their purchases to split […]
If you are working as a Data Analyst or a Data scientist as I do, or if you are learning to be one, You should be familiar with the fact that data comes at a breakneck speed and Data Scientist and Analysts are meant to handle the data that is most numerical and categorical. But […]
Many Business activities are seasonal in nature, where most of the business are dependent on a particular time of festival and holidays. Every business uses sales promotion techniques to increase the demand for their products and services, in order to stay in the market for a longer period. In this article, I am going to […]
TensorFlow is a powerful library for numerical computation, particularly well suited and fine-tuned for large–scale Machine Learning ( but you could use it for anything else that requires heavy calculations). The Google Brain team developed it, and it powers many of Google’s large-scale services, such as Google cloud speech, Google Photos, and Google Search. It […]
Reinforcement Learning (RL) is one of the most exciting fields of machine learning today. and also one the oldest. It has been around since the 1950s, producing many exciting applications over the years, particularly in games (e.g., TD-Gammon, a Backgammon-playing program) and in machine control, but seldom making the headline news. But a revolution took […]
Merging Datasets is one of the most high-performance features, which is provided by pandas in Python. In this article, I will show how we can merge datasets in Python with the help of examples and real-world scenarios. For convenience, I will define a display function: Categories of Merging Datasets Pandas is blessed with a function […]
Evaluating a model is simple enough to use a test set. But suppose you are hesitating in model selection between two types of models (say, a linear model and a polynomial model); how can you decide between them? One option is to train both and compare how well they generalize using the test set. How […]
There is a lot of difference between the data you get to practice data science skills and the data you get in the real world. Honestly speaking, many datasets you will get in the process of actual-world data science tasks will always come with some amount of missing data. Sometimes it gets tough when different […]
One week ago, Dr Cohen started collecting X-ray images of COVID 19 cases and publishing them in the following GitHub repo, for the work of COVID 19 detection. Inside the repo you’ll find example of COVID-19 cases, as well as MERS, SARS, and ARDS. In order to create the COVID 19 X-ray image dataset for this Article, […]
This article is about description for those who need to know what is the actual difference between the dataset split between the Training and Test sets in Machine Learning while training and classifying models. What is Training Data? All the machine learning algorithms learn from data by finding relationships, developing understanding, making decisions, and building […]
Rotating, re-orienting, or stretching the piece of paper in three-dimensional space doesn’t change the flat geometry of the article: such operations are akin to linear embeddings. If you bend, curl, or crumple the paper, it is still a two-dimensional manifold, but the embedding into the three-dimensional space is no longer linear. Manifold learning algorithms would […]
In this article, you will explore what is perhaps one of the most broadly used of unsupervised algorithms, principal component analysis (PCA). PCA is fundamentally a dimensionality reduction algorithm, but it can also be useful as a tool for visualization, for noise filtering, for feature extraction and engineering, and much more. After a brief conceptual […]
Below are some of the famous Data Science books that will help beginners explore more about Data Science and the experienced practitioners to gain more deep knowledge. I found these books really useful and highly recommended. Best Data Science Books Here are the top 7 books that will help you gain a more in-depth knowledge […]
Data Science and Data Analysis have been around a lot this year. For students who are looking for a long term career, both Data Science and Data Analysis jobs have been a good option for them. We will see this trend continuing as the future is all about AI and Machine Learning. Today every activity […]
Decision Trees are versatile Machine Learning algorithms that can perform both classification and regression tasks, and even multi-output tasks. They are powerful algorithms, capable of fitting complex datasets. Decision trees are also the fundamental components of Random Forests, which are among the most powerful Machine Learning algorithms available today. In this article, I will start […]
Support vector machines (SVMs) are a particularly powerful and flexible class of supervised algorithms for both classification and regression. In this article, I will develop the intuition behind support vector machines and their use in classification problems. I will begin with the standard imports: Motivating Support Vector Machines Let’s consider the simple case of a […]
In Machine Learning Naive Bayes models are a group of high-speed and simple classification algorithms that are often suitable for very high-dimensional datasets. Because they are so fast and have so few tunable parameters, they end up being very useful as a quick-and-dirty baseline for a classification problem. This article will focus on an intuitive […]
This Workflow can guide you through your Machine Learning Projects. There are eight main steps: Frame the problem and look at the big picture. Get the data. Explore the data to get insights. Prepare the data to better expose the underlying data patterns to machine learning algorithms. Explore many different models and shortlist the best […]
What is a Neural Network Neural Network is a computational algorithm that is used in creating deep learning models for predictions and classifications. It is based on self-learning and training, rather than being explicitly programmed. Neural Networks are inspired by the central nervous system of human beings; neural networks have connected nodes that are very […]
In the real world, data rarely comes in perfect form. With this in mind, one of the more critical steps in using machine learning in practice is Feature Engineering, that is, taking whatever information you have about your problem and turning it into numbers that you can use to build your feature matrix. What is Feature […]
Machine Learning interview questions are an essential part of an interview as a Data Scientist. Here I have created a set of Machine Learning interview question with there answers along. With these questions and solutions, you will be able to do well in your interview based on Machine Learning. Machine Learning Interview Questions: How would […]