Notions on machine learning

This repository contains some terminology and descriptions of several aspects regarding machine learning.

Table of contents

• Machine learning
• Popular algorithms
  • Linear Regression
  • Logistic Regression
  • Naive Bayes
  • Neural Networks
  • Decision Trees
  • Support vector machines
  • Clustering
• More on neural networks
  • Definitions
  • Activation functions
  • Optimization
    • Weight initialization
    • Dropout
    • Regularization
    • Gradient descent with momentum
    • Learning rate decay

Sources

• Books
  • Real-world machine learning, H.Brink, J. W. Richards, M. Fetherolf, Manning Publications, 2016
  • Machine learning: the art and science of algorithms that make sense of data, Peter Flach, Cambridge University Press, 2012
  • Neural networks and deep learning, Michael A. Nielsen, Determination Press, 2015
  • Deep learning with python, F. Chollet, Manning Publications, 2017
• Videos
  • Machine learning by Andrew Ng
  • Deep learning by Andrew Ng
  • Stanford Lecture - Convolutional neural networks for visual recognition
• Blogs
  • elitedatascience.com
  • machinelearningmastery.com
• The countless sources available over the internet that are helping to advance the machine learning community