ML Algorithms from scratch in Python

Self notes for behind the scenes mathematical understanding

Goal: To build Machine Learning algorithms in python without using any over-the-shelf ML library like SKLearn or Tensorflow. Intend to cover Linear Regression, Logistic Regression, KNN, K-Means Clustering, Decision Trees, Random Forest, SVM, XGBoost, Perceptron, Neural Net with Backpropagation, DNN, RNN, LSTM, TF-IDF, Bag Of Words, LDA, and Word2Vec.

Linear Regression