Machine Learning: A Complete and Detailed Overview

The 10 Algorithms Machine Learning 
http://www.kdnuggets.com/2016/08/10-algorithms-machine-learning-engineers.html

 Support Vector Machines

Naïve Bayes Classification

Decision Trees

Ordinary Least Squares Regression

Logistic Regression

Ensemble Methods

Clustering Algorithms

Principal Component Analysis

Independent Component Analysis

Singular Value Decomposition.

This is an overview (with links) to a 5-part series on introductory machine learning. The set of tutorials is comprehensive, yet succinct, covering many important topics in the field (and beyond).

Chapters

1. Overview, goals, learning types, and algorithms
2. Data selection, preparation, and modeling
3. Model evaluation, validation, complexity, and improvement
4. Model performance and error analysis
5. Unsupervised learning, related fields, and machine learning in practice

http://www.innoarchitech.com/machine-learning-an-in-depth-non-technical-guide/?utm_source=innoarchitech&utm_medium=post&utm_content=chapterlink&utm_campaign=blog