Master Machine Learning Algorithms

You must understand the algorithms to get good (and be recognized as being good) at machine learning.

In this mega Ebook written in the friendly Machine Learning Mastery style that you’re used to, finally cut through the math and learn exactly how machine learning algorithms work, then implement them from scratch, step-by-step.

This Ebook is 163 pages.
PDF format.

Gentle introductions 10 top machine learning algorithms.
12 step-by-step tutorials with every snippet of math explained with a worked example using real numbers.
Includes 16 spreadsheets with a working implementation of each machine learning algorithm.

Let’s take a look at which machine learning algorithms are covered in the Ebook:

Linear Algorithms:

Algorithm 1: Linear Regression
Algorithm 2: Logistic Regression
Algorithm 3: Linear Discriminant Analysis
Nonlinear Algorithms:

Algorithm 4: Classification and Regression Trees
Algorithm 5: Naive Bayes
Algorithm 6: K-Nearest Neighbors
Algorithm 7: Learning Vector Quantization
Algorithm 8: Support Vector Machines
Ensemble Algorithms:

Algorithm 9: Bagged Decision Trees and Random Forest
Algorithm 10: Boosting and AdaBoost
Bonus #1: Gradient Descent

The Gradient Descent algorithm is also covered as it us used as the optimization algorithm at the core of so many machine learning algorithms.