A Tour of Machine Learning Algorithms - Jason Brownlee
Understanding the Bias-Variance Tradeoff - Scott Fortmann-Roe
An overview of gradient descent optimization algorithms - Sebastian Ruder
Understanding objective functions in neural networks - Lars hulstaert
Implement t-SNE in Python and Numpy
Dimensionality reduction for MNIST
A Kaggle Master Explains Gradient Boosting - Ben Gorman
Introduction to Boosted Trees (XGBoost)
How To Implement The Decision Tree Algorithm From Scratch In Python - Jason Brownlee
A Beginner's Guide To Understanding Convolutional Neural Networks - Adit Deshpande
Analysis of Dropout - Paolo Galeone
Demystifying Deep Reinforcement Learning - Tambet Matiisen
An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec
scikit-learn: A tutorial on statistical-learning for scientific data processing
Machine Learning Algorithm Recipes in scikit-learn - Jason Brownlee
ANN tutorial - Brian Dolhansky
Machine Learning for Humans - Vishal Maini
Bayseian Neural Network for MNIST
Convolutional Neural Networks for Visual Recognition - Andrej Karpathy - CS231n (2016)