Dive into ML

In this repository, I shall be keeping my Jupyter Notebooks while diving into Machine Learning. Implementations of some algorithms are done from scratch while each of them is implemented using Sklearn as well.

This Repository includes:

1. Introduction to Python
2. Advanced Python and Machine Learning Tools - SciKit Learn, Pandas, Matplotlib
3. Introduction to Machine Learning
4. Supervised Learning Algorithms
5. Linear Regression
6. Multivariable Regression
7. Gradient Descent
8. Classification

   • Measures:

     • Confusion Metrics
     • Classification Report

   • Algorithms:

     • Principal Component Analysis
     • Decision Trees
     • Random Forest
     • Naive Bayes
     • K Nearest Neighbours (KNN)
     • Support Vector Machine (SVM)
     • Principal Component Analysis (PCA)

and still working on...

Clone the Repo:

git clone https://github.com/wikiabhi/Dive-into-ML.git

MIT License Copyright (c) 2018 Abhishek