Machine Learning Algorithms From Scratch: With Phython

✍ Scribed by Jason Brownlee

• Publisher: Independently Published
• Year: 2018
• Tongue: English
• Leaves: 237
• Series: Machine Learning Mastery
• Edition: 1.7
• Category: Library

✦ Synopsis

You must understand algorithms to get good at machine learning. The problem is that they are only ever explained using Math. No longer.

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.

Using clear explanations, simple pure Python code (no libraries!) and step-by-step tutorials you will discover how to load and prepare data, evaluate model skill, and implement a suite of linear, nonlinear and ensemble machine learning algorithms from scratch.

✦ Table of Contents

Copyright
Welcome
I Data Preparation
Load Data From CSV
Description
Tutorial
Extensions
Review
Scale Machine Learning Data
Description
Tutorial
Extensions
Review
Algorithm Evaluation Methods
Description
Tutorial
Extensions
Review
Evaluation Metrics
Description
Tutorial
Extensions
Review
Baseline Models
Description
Tutorial
Extensions
Review
II Linear Algorithms
Algorithm Test Harnesses
Description
Tutorial
Extensions
Review
Simple Linear Regression
Description
Tutorial
Extensions
Review
Multivariate Linear Regression
Description
Tutorial
Extensions
Review
Logistic Regression
Description
Tutorial
Extensions
Review
Perceptron
Description
Tutorial
Extensions
Review
III Nonlinear Algorithms
Classification and Regression Trees
Descriptions
Tutorial
Extensions
Review
Naive Bayes
Descriptions
Tutorial
Extensions
Review
k-Nearest Neighbors
Description
Tutorial
Extensions
Review
Learning Vector Quantization
Description
Tutorial
Extensions
Review
Backpropagation
Description
Tutorial
Extensions
Review
IV Ensemble Algorithms
Bootstrap Aggregation
Descriptions
Tutorial
Extensions
Review
Random Forest
Description
Tutorial
Extensions
Review
Stacked Generalization
Description
Tutorial
Extensions
Review
V Conclusions
How Far You Have Come
Getting More Help
Machine Learning Books
Forums and Q&A Websites
Contact the Author
VI Appendix
Standard Datasets
Overview
Swedish Auto Insurance Dataset
Wine Quality Dataset
Pima Indians Diabetes Dataset
Sonar Dataset
Banknote Dataset
Iris Flower Dataset
Abalone Dataset
Ionosphere Dataset
Wheat Seeds Dataset
Python Crash Course
Assignment
Flow Control
Data Structures