40 Machine Learning Algorithms with Python

2 min readJun 14, 2021

All Machine Learning Algorithms and models explained with Python.

In this article, I will take you through an explanation and implementation of all Machine Learning algorithms with Python programming language.

Machine learning algorithms are a set of instructions for a computer on how to interact with, manipulate, and transform data. There are so many types of machine learning algorithms. Selecting the right algorithm is both science and art.

All Machine Learning Algorithms with Python

  1. DBSCAN Clustering
  2. Naive Bayes
  3. Gradient Boosting(Used in implementing the Instagram Algorithm)
  4. Logistic Regression
  5. Linear Regression
  6. Apriori Algorithm
  7. K Nearest Neighbor
  8. CatBoost
  9. SMOTE
  10. Hypothesis Testing(Commonly used in Outlier Detection)
  11. Tf-IdfVectorization
  12. Cross-Validation
  13. 4-Graph-Algorithms (Connected Components, Shortest Path, Pagerank, Centrality Measures)
  14. Ridge and Lasso Regression
  15. StandardScaler
  16. SARIMA
  17. ARIMA
  18. XGBoost Algorithm
  19. Long Short Term Memory (LSTM)
  20. One Hot Encoding
  21. Bidirectional Encoder Representations from Transformers (BERT)
  22. Facebook Prophet
  23. NeuralProphet
  24. AdaBoost Algorithm
  25. Random Forest Algorithm
  26. H2O AutoML
  27. Polynomial Regression
  28. Gradient Descent Algorithm
  29. Grid Search Algorithm
  30. K-Means Algorithm
  31. Manifold Learning
  32. Principal Component Analysis
  33. Decision Trees
  34. Support Vector Machines
  35. Neural Networks
  36. FastAI
  37. LightGBM

All the above algorithms are explained properly by using the python programming language. These were the common and most used machine learning algorithms. We will update this article with more algorithms soon. I hope you liked this article on all machine learning algorithms with Python programming language. Feel free to ask your valuable questions in the comments section below.