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Master Machine Learning Algorithms

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Description

 							
  
  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. 						

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