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The Machine Learning project including ML/DL projects, notebooks, cheat codes of ML/DL, useful information on AI/AGI and codes or snippets/scripts/tasks with tips.
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With the start of 100DaysOfMLCode challenge this Machine Learning Goodness repository is updated daily with either the completed Jupyter notebooks, Python codes, ML projects, useful ML/DL/NN libraries, repositories, cheat codes of ML/DL/NN/AI, useful information such as websites, beneficial learning materials, tips and whatnot not to mention some basic and advanced Python coding.
As the challenge is over the repo still grows. New beneficial material or materials in the world of Machine Learning when found is/are added to books, tools or repositories as well as updated in FinishYearWithML challenge and tweeted through my Twitter account and on Linkedin as well as sometimes on Facebook, Instagram.
Worthy books to hone expertise of ML/DL/NN/AGI, Python Programming, CS fundamentals needed for AI analysis and any useful book for a Developer or ML Engineer.
| Number | Title | Description | Link |
|---|
| 1 | Grokking Algorithms: An illustrated guide for programmers and other curious people | Visualisation of most popular algorithms used in Machine Learning and programming to solve problems | Grokking Algorithms |
| 2 | Algorithm Design Manual | Introduction to mathematical analysis of a variety of computer algorithms | Algorithm Design Manual |
| 3 | Category Theory for Programmers | Book about Category Theory written on posts from Milewski's programming cafe | Category Theory for Programmers |
| 4 | Automated Machine Learning | Book includes overviews of the bread-and-butter techniques we need in AutoML, provides in-depth discussions of existing AutoML systems, and evaluates the state of the art in AutoML | Automated Machine Learning |
| 5 | Mathematics for Computer Science | Book by MIT on Mathematics for Computer Science | Mathematics for Computer Science |
| 6 | Mathematics for Machine Learning | Book by University of California on Mathematics for Machine Learning | Mathematics for Machine Learning |
| 7 | Applied Artificial Intelligence | Book on engineering AI applications | Applied Artificial Intelligence |
| 8 | Automating Machine Learning Pipeline | Book-overview of automating ML lifecycle with Databricks Lakehouse platform | Automating Machine Learning Pipeline |
| 9 | Machine Learning Yearning | The book for AI Engineers win the era of Deep Learning | Machine Learning Yearning |
| 10 | Think Bayes | An introduytion to Bayesian statistics with Python implementation and Jupyter Notebooks | Think Bayes |
| 11 | The Ultimate ChatGPT Guide | The book that provides 100 resources to enhance your life with ChatGPT | The Ultimate ChatGPT Guide |
| 12 | The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts | The book to learn strategies for crafting compelling ChatGPT prompts that drive engaging and informative conversations | The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts |
| 13 | 10 ChatGPT prompts for Software Engineers | The book to learn how to prompt for software engineering tasks | 10 ChatGPT prompts for Software Engineers |
| 14 | How to Build Your Career in AI | Andrew Ng's insights about learning foundational skills, working on projects, finding jobs, and community in machine | How to Build Your Career in AI |
| 15 | Machine Learning Q and AI | Th book on popular wuestions asked in interviews on ML and advanced information to those questions | Machine Learning Q and AI |
| 16 | A comprehensive guide to Machine Learning | A free book of comprehensive guide to ML | A comprehensive guide to Machine Learning |
| 17 | Math for Deep Learning: What You Need to Know to Understand Neural Networks | A book of Mathematics for Machine Learning and Artificial Intelligence that goes into the Mathematics & Statistics Foundations of for Data Science | Math for Deep Learning: What You Need to Know to Understand Neural Networks |
Worthy websites and tools that include cheat codes for Python, Machine Learning, Deep Learning, Neural Networks and what not apart from other worthy tools while you are learning or honing your skills can be found here. Updated constantly when a worthy material is found to be shared on the repository.
| Number | Title | Description | Link