# machine-learning-yearning

**Repository Path**: jinjun/machine-learning-yearning

## Basic Information

- **Project Name**: machine-learning-yearning
- **Description**: Machine Learning Yearning book by  🅰️𝓷𝓭𝓻𝓮𝔀 🆖
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2025-06-08
- **Last Updated**: 2025-06-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<p align="center"><img src="/images/mly.png"></p>

# Machine Learning Yearning &nbsp;[![Tweet](https://img.shields.io/twitter/url/http/shields.io.svg?style=social)](https://twitter.com/intent/tweet?text=Machine%20Learning%20Yearning%2C%20book%20by%20Andrew%20Ng%20&url=https://github.com/ajaymache/machine-learning-yearning&hashtags=machinelearning,ML,AI,deeplearning,andrewng,coursera,datascience)&nbsp;&nbsp;![license](/shields/license-free-orange.svg)&nbsp;&nbsp;[![GitHub issues](https://img.shields.io/github/issues/ajaymache/travis-ci-with-github.svg?colorB=99cc33)](https://github.com/ajaymache/travis-ci-with-github/issues)&nbsp;&nbsp;![Contributions](/shields/contributions.svg)

#### Technical Strategy for AI Engineers, In the Era of Deep Learning

Author : 🅰️𝓷𝓭𝓻𝓮𝔀 🆖
### About

The book has been divided into 13 parts originally by _**Prof. Andrew NG**_ along with the complete book with all the parts consolidated. In this book you will learn how to align on ML strategies in a team setting, as well as how to set up development (dev) sets and test sets. Recommendations for how to set up dev/test sets have been changing as Machine Learning is moving toward bigger datasets, and this explains how you should do it for modern ML projects.

### Contents
:zero::zero: [Full Book](/full%20book/machine-learning-yearning.pdf)  

:zero::one: [Chapters 1 to 14](machine-learning-yearning-part1.pdf)

:zero::two: [Chapters 15 to 19](machine-learning-yearning-part2.pdf)

:zero::three: [Chapters 20 to 22](machine-learning-yearning-part3.pdf)

:zero::four: [Chapters 23 to 27](machine-learning-yearning-part4.pdf)

:zero::five: [Chapters 28 to 30](machine-learning-yearning-part5.pdf)

:zero::six: [Chapters 31 to 32](machine-learning-yearning-part6.pdf)

:zero::seven: [Chapters 33 to 35](machine-learning-yearning-part7.pdf)

:zero::eight: [Chapters 36 to 39](machine-learning-yearning-part8.pdf)

:zero::nine: [Chapters 40 to 43](machine-learning-yearning-part9.pdf)

:one::zero: [Chapters 44 to 46](machine-learning-yearning-part10.pdf)

:one::one: [Chapters 47 to 49](machine-learning-yearning-part11.pdf)

:one::two: [Chapters 50 to 52](machine-learning-yearning-part12.pdf)

:one::three: [Chapters 53 to 58](machine-learning-yearning-part13.pdf)