This is a collection of python notebooks discussing/illustrating some introductory or interesting concepts in machine learning. I will keep on updating this repository when I learn or come across interesting topic. Some of the topics covered so far include:
- Exploratory data analysis
- Linear algebra
- k-Nearest Neighbors classifier
- Hidden Markov Model
- Linear regression
- Naive-Bayes Classifier
- Logistic Regression
- Logistic Regression implementation in Tensorflow
- Support Vector Machines
- Probability and statistics