Machine Learning: Step-by-Step Guide To Implement Machine Learning Algorithms with Python

**MACHINE LEARNING - PYTHONBuy the Paperback version of this book, and get the Kindle eBook version included for FREE!** Do You Want to Become An Expert Of Machine Learning?? Start **Getting this Book and Follow My Step by Step Explanations! Click Add To Cart Now!**This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a practical way, and we'll implement many machine-learning algorithms using the Scikit-learn library in the Python programming language. In the first chapter, you'll learn the most important concepts of machine learning, and, in the next chapter, you'll work mainly with the classification. In the last chapter you'll learn how to train your model. I assume that you've knowledge of the basics of programming This book contains **illustrations** and **step-by-step explanations with bullet points** and **exercises** for easy and enjoyable learning. Benefits of reading this book that you're not going to find anywhere else: * Introduction to Machine Learning * Classification * How to train a Model * Different Models Combinations Don't miss out on this new step by step guide to Machine Learning. All you need to do is scroll up and click on the **BUY NOW** button to learn all about it! CHAPTER 1 6 INTRODUCTION TO MACHINE LEARNING 6 Theory 7 What is machine learning? 8 Why machine learning? 9 When should you use machine learning? 12 Types of Systems of Machine Learning 13 Supervised and unsupervised learning 14 Supervised Learning 14 The most important supervised algorithms 15 Unsupervised Learning 15 The most important unsupervised algorithms 15 Reinforcement Learning 17 Batch Learning 18 Online Learning 19 Instance based learning 20 Model-based learning 21 Bad and Insufficient Quantity of Training Data 22 Poor-Quality Data 23 Irrelevant Features 24 Feature Engineering 24 Testing 25 Overfitting the Data 26 Solutions 26 Underfitting the Data 27 Solutions 27 EXERCISES 28 SUMMARY 29 REFERENCES 30 CHAPTER 2 31 CLASSIFICATION 31 Installation 32 The MNIST 33 Measures of Performance 37 Confusion Matrix 39 Recall 41 Recall Tradeoff 42 ROC 44 Multi-class Classification 46 Training a Random Forest Classifier 47 Error Analysis 48 Multi-label Classifications 51 Multi-output Classification 52 EXERCISES 53 REFERENCES 55 CHAPTER 3 56 HOW TO TRAIN A MODEL 56 Linear Regression 57 Computational Complexity 60 Gradient Descent 61 Batch Gradient Descent 64 Stochastic Gradient Descent 66 Mini-Batch Gradient Descent 68 Polynomial Regression 69 Learning Curves 71 Regularized Linear Models 72 Ridge Regression 72 Lasso Regression 72 EXERCISES 74 SUMMARY 75 REFERENCES 76 Chapter 4 77 Different models combinations 77 Implementing a simple majority classifer 83 Combining different algorithms for classification with majority vote 90 Questions 103 MACHINE LEARNING - PYTHON Buy the Paperback version of this book, and get the Kindle eBook version included for FREE! Do You Want to Become An Expert Of Machine Learning?? Start Getting this Book and Follow My Step by Step Explanations! Click Add To Cart Now! This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a practical way, and we'll implement many machine-learning algorithms using the Scikit-learn library in the Python programming language. In the first chapter, you'll learn the most important concepts of machine learning, and, in the next chapter, you'll work mainly with the classification. In the last chapter you'll learn how to train your model. I assume that you've knowledge of the basics of programming This book contains illustrations and step-by-step explanations with bullet points and exercises for easy and enjoyable learning. Benefits of reading this book that you're not going to find anywhere else: Introduction to Machine Learning Classification How to train a Model Different Models Combinations Don't miss out on this new step by step guide to Machine Learning. All you need to do is scroll up and click on the BUY NOW button to learn all about it!