Machine Learning: Machine Learning is a method of teaching machines/computers to make a prediction based on some data and experien...

Data Preprocessing: Data Prepossessing is the first stage of building a machine learning model. It involves transforming raw data...

Regression: Basically, Regression is a statistical approach to find the correlations between variables(dependent and independent)....

Simple Linear Regression: It is a linear regression model that uses two-dimensional sample points with one independent and one dep...

Multiple Linear Regression: Multiple Linear Regression is closely related to a simple linear regression model with the difference...

Polynomial Regression: Polynomial regression is a form of regression analysis in which the relationship between the independent va...

Support Vector Regression: Support Vector Regression(SVR) is quite different than other Regression models. It uses Support Vector...

Decision Tree Regression: This Regression is based on the decision tree structure. A decision tree is a form of a tree or hierarch...

Random Forest Regression: The basic idea behind Random Forest is that it combines multiple decision trees to determine the final o...

The performance of a regression model can be understood by knowing the error rate of the predictions made by the model. You can al...

Classification: Classification is machine learning task of predicting the value of a categorical variable(target or class). This i...

In this article, I will go you through the logistic regression, a simple classification algorithm. Then we will implement the algo...

In this tutorial, I am going to explain to you the K-Nearest Neighbor(KNN) algorithm and how to implement this algorithm in Python...

In this tutorial, we will learn the Support Vector Machine algorithm and implement it in Python. Support Vector Machine: Support...

In this tutorial, we are going to introduce to the Kernel Support Vector Machine and how to implement in Python. Kernel SVM Intui...

In this tutorial, we are going to learn the intuition behind the Naive Bayes classification algorithm and implement it in Python....

In this article, we are going to understand the concept of Decision Tree algorithm for classification and then we will implement i...

Random Forest is an ensemble learning technique. It builds a number of decision trees on the randomly selected data sample. Then i...

Evaluating Classification Model performance: This section consists of different types of tutorial. Here given below: False posi...

Clustering: Clustering is similar to classification, but the basis is different. In Clustering, you don't know what you are lookin...

Hierarchical Clustering: Hierarchical clustering is where you build a cluster tree (a dendrogram) to represent data, where each gr...

Association Rule Learning: In this part, you will understand and learn how to implement the following Association Rule Learning mo...

Eclat Intuition: Today, we are talking about the Eclat model. It is similar to the a priori algorithm. Here, we actually talking a...

Reinforcement Learning: Reinforcement Learning is a branch of Machine Learning, also called Online Learning. It is used to solve i...

In this tutorial, I will explain to you the application of Upper Confidence Bound(UCB) algorithm to solve the Multi Bandit problem...

In this article, we will talk about the Thompson Sampling Algorithm for solving the multi-armed bandit problem and implement the a...

Natural Language Processing: Natural language processing (NLP) is a field of computer science concerned with the interactions betw...

Deep Learning: Deep Learning is an artificial intelligence function that imitates the workings of the human brain in processing da...

Artificial Neural Networks: An artificial neural network (ANN), usually called Ã¢â‚¬Å“neural...

Dimensionality Reduction: Dimensionality Reduction is the process of reducing the number of random variables under consideration b...

Linear Discriminant Analysis (LDA): LDA is used as a dimensionality reduction technique. It is used in the preprocessing step for...

Kernel PCA in python: Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extract...

Model Selection & Boosting: Model Selection is the undertaking of choosing a statistical model from an arrangement of candidat...

K-fold cross Validation: Cross-validation, sometimes called rotation estimation, or out-of-sample testing is any of various simila...

XGBoost in Python Step 1: First of all, we have to install the XGBoost. Now, we need to implement the classification problem. In t...

Convolution Neural Network: A Convolutional neural network (CNN, or ConvNet) is a class of deep, feed-forward artificial neural ne...