Machine Learning_ Step-by-Step Guide To Implement Machine Learning Algorithms with Python_Rudolph Russell.pdf

Machine Learning Step-by-Step Guide To Implement Machine Learning Algorithms with Python Author Rudolph Russell ©Copyright 2018 - All rights reserved. If you would like to share this book with another person, please purchase an additional copy for each recipient. Thank you for respecting the hard work of this author. Otherwise, the transmission, duplication or reproduction of any of the following work including specific information will be considered an illegal act irrespective of if it is done electronically or in print. This extends to creating a secondary or tertiary copy of the work or a recorded copy and is only allowed with an express written consent from the Publisher. All additional right reserved. Table of Contents CHAPTER 1 INTRODUCTION TO MACHINE LEARNING Theory What is machine learning? Why machine learning? When should you use machine learning? Types of Systems of Machine Learning Supervised and unsupervised learning Supervised Learning The most important supervised algorithms Unsupervised Learning The most important unsupervised algorithms Reinforcement Learning Batch Learning Online Learning Instance based learning Model-based learning Bad and Insufficient Quantity of Training Data Poor-Quality Data Irrelevant Features Feature Engineering Testing Overfitting the Data Solutions Underfitting the Data Solutions EXERCISES SUMMARY REFERENCES CHAPTER 2 CLASSIFICATION Installation The MNIST Measures of Performance Confusion Matrix Recall Recall Tradeoff ROC Multi-class Classification Training a Random Forest Classifier Error Analysis Multi-label Classifications Multi-output Classification EXERCISES REFERENCES CHAPTER 3 HOW TO TRAIN A MODEL Linear Regression Computational Complexity Gradient Descent Batch Gradient Descent Stochastic Gradient Descent Mini-Batch Gradient Descent Polynomial Regression Learning Curves Regularized Linear Models Ridge Regression Lasso Regression EXERCISES SUMMARY REFERENCES Chapter 4 Different models