How To Explain Each Machine Learning Model In Brief

In this blog, I want to share a resource that provides concise explanations of all machine learning models ranging from Simple Linear regression to XGBoost to Clustering techniques.

Models Covered

1. Linear Regression
2. Polynomial Regression
3. Ridge Regression
4. Lasso Regression
5. Elastic Regression
6. Logistic Regression
7. K Nearest-Neighbors
8. Naive Bayes
9. Support Vector Machines
10. Decision Trees
11. Random Forest
12. Extra Trees
13. Gradient Boost
14. Ada Boost
15. XGBoost
16. K Means Clustering
17. Hierarchical Clustering
18. DBSCAN Clustering
19. Apriori
20. PCA

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