ML Algorithms from scratch in Python

Author(s): Ravi Shankar

Originally published on Towards AI.

Self notes for behind the scenes mathematical understanding

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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.

Gradient Descent is the process of minimizing a function by following the gradients of the cost function. This involves knowing the form of the cost as well as the derivative so that from a given point you know the gradient and… Read the full blog for free on Medium.

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Published via Towards AI