Machine Learning Algorithms Guide

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 classifications based on the patterns they have learned from the data. If you want to learn all ML algorithms, this article is for you. In this article, I’ll take you through a guide to all Machine Learning algorithms solved and explained using Python.

All Machine Learning Algorithms Guide

Below is a list of all Machine Learning algorithms linked with an appropriate guide to learn the concepts and their implementation using Python.

Regression Algorithms

• Linear Regression
• Polynomial Regression
• Ridge and Lasso Regression
• Elastic Net Regression

Linear Classification Algorithms

• Logistic Regression
• Linear Discriminant Analysis (LDA)
• Stochastic Gradient Descent Classifier

Naive Bayes Algorithms

• How Naive Bayes Works
• Gaussian Naive Bayes
• Multinomial Naive Bayes
• Bernoulli Naive Bayes

SVM and KNN Algorithms

• Support Vector Machines
• K Nearest Neighbours

Decision Trees and Ensemble Methods

• Decision Trees
• Cart, ID3, and C4.5
• Random Forests

Boosting Algorithms

• Gradient Boosting
• Adaboost

Clustering Algorithms

• K-means Clustering
• DBSCAN
• Agglomerative Clustering
• BIRCH Clustering
• Mean Shift Clustering

Neural Network Architectures

• Perceptron
• Multilayer Perceptron
• CNN
• RNN
• LSTM
• GAN
• Transformer Networks

Time Series

• ARIMA and SARIMA

So this was a guide to all the most important Machine Learning algorithms you should know about as a Data Scientist or an ML Engineer. Each algorithm in the list is linked to a guide that will help you learn the concept behind the algorithm with implementation using Python. You can also follow my book on Machine Learning algorithms shown below to learn about all Machine Learning algorithms and essential concepts in detail step by step.

Summary

The above list will keep updating with more concepts and algorithms. ML algorithms are computational procedures that enable machines to learn patterns and relationships from data without being explicitly programmed. I hope you liked this article on a list of all Machine Learning algorithms solved and explained using Python. Feel free to ask valuable questions in the comments section below.