This repository shows how to implement the basic machine learning methods using numpy rather than the exsiting and converient library, in order to understand the underlying theorems of ML.

The reference Textbook is:

1. Pattern Recognition And Machine Learning

A list of ML methods to be implemented is given below.

1. K-Nearest Neighbors
2. Naive Bayes
3. Linear Regression
4. Logistic Regression
5. Gaussian Process Regression (using kernel)
6. K-means Clustering
7. Hidden Markov Model
8. Deep Neural Network