/ML-Cheatsheet

These are my notes for machine learning

Primary LanguageJupyter Notebook

Machine Learning Cheat Sheet

These Notebooks Contain:

  • Explaining Various machine learning algorithms concepts and implementing them using libraries like scikit learn.
  • Implementing various machine learning algorithms from scratch:
    • Logistic Regression
    • KNN
    • Decision Tree
    • Gaussian Mixture Models
    • LDA
    • QDA
    • Naive Bayes
    • PCA
  • How to use Pandas and Scikit Learn libraries for data wrangling and preprocessing.
  • How to perform hyperparameter tuning using various methods and packages.
  • Explanation for Feature Engineering, Feature Selection, and Feature Extraction and how to implement some of these methods.

NOTE: there is no deep learning here.
NOTE: still ongoing project (last update: August 2022)