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Machine Learning Goodness with various repositories or notebooks , ML/DL projects and AGI/AI tips/cheats.
Overview & Next Move
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.
Table of Contents
- Table of contents
- Worthy Books
- Worthy Tools
- Worthy Repositories
- Notebooks
- Notes
- 100DaysOfMLCode
- FinishYearWithML
- Public
- Jupyter in Browser
- Logo
- License
Worthy Books
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 Tools
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 |
|---|---|---|---|
| 1 | Python Cheatsheet | The Python Cheatsheet based on the book "Automate the Boring Stuff with Python" and many other sources | Python Cheatsheet |
| 2 | Machine Learning Algorithms Cheatsheet | The Machine Learning Cheatsheet explaining various models briefly | ML Algorithms Cheatsheet |
| 3 | Awesome AI Datasets & Tools | Links to popular open-source and public datasets, data visualizations, data analytics resources, and data lakes | Awesome AI Datasets & Tools |
| 4 | Machine Learning Cheatsheet | This Cheatsheet contains many classical equations and diagrams on Machine Learning to quickly recall knowledge and ideas on Machine Learning | Machine Learning Cheatsheet |
| 5 | Universal Intelligence: A Definition of Machine Intelligence | The publication on definitions of intelligence | Universal Intelligence |
| 6 | Logistic Regression | Detailed Overview of Logistic Regression | Logistic Regression |
| 7 | BCI Overview | Simple Overview of Brain-Computer Interface (BCI) | BCI Overview |
| 8 | BCI Research | Fascinating research of Brain-Computer Interface (BCI) | BCI Research |
| 9 | AI in Chemical Discovery | How AI is changing Chemical Diccovery? | AI in Chemical Discovery |
| 10 | Machine Learning for Chemistry | Best practices in Machine Learning for Chemistry | Machine Learning for Chemistry |
| 11 | AI tools for drug discovery | 5 cool AI-powered Drug Discovery tools | AI tools for drug discovery |
| 12 | Quantum Chemistry and Deep Learning | The application of Deep Learning and Neural Networks on Quantum Chemisty | Quantum Chemistry and Deep Learning |
| 13 | Computing Machinery and Intelligence | First paper on AI by Alan Turing | Computing Machinery and Intelligence |
| 14 | The blog on the take of Alan Turing | The analysis of Alan Turing's paper on AI (13 in the list) and the blog post on the life of him | Blog on Alan Turing |
| 15 | Minds, Brains and Programs | Paper that objects 'Turing Test' by John Searle | Minds, Brains and Programs |
| 16 | The blog on the take Of John Searle & Alan Turing | The blog post on the take Of John Searle paper (15 in the list) and ideas about AI and Alan Turing | John Searle & Alan Turing |
| 17 | The Youtube channel on Deep Learning's Neural Networks | An amazing youtube channel explaining what is Neural Network with simple and easy to follow descriptions | Deep Learning's Neural Networks |
| 18 | 8 architectures of Neural Networks | 8 architectures of Neural Network every ML engineer should know | 8 architectures |
| 19 | Neural Networks for the Prediction of Organic Chemistry Reactions | The use of neural networks for predicting reaction types | NNs for Prediction of Organic Chemistry Reactions |
| 20 | Expert System for Predicting Reaction Conditions: The Michael Reaction Case | Models were built to decide the compatibility of an organic chemistry process with each considered reaction condition option | Expert System for Predicting Reaction Conditions |
| 21 | Machine Learning in Chemical Reaction Space | Looked at reaction spaces of molecules involved in multiple reactions using ML-concepts | Machine Learning in Chemical Reaction Space |
| 22 | Machine Learning for Chemical Reactions | An overview of the questions that can and have been addressed using machine learning techniques | Machine Learning for Chemical Reactions |
| 23 | ByTorch overview | BoTorch as a framework of PyTorch | ByTorch overview |
| 24 | ByTorch official | Bayesian optimization or simply an official website of BoTorch | ByTorch official |
| 25 | VS Code Cheatsheet | VS Code Shortcut Cheatsheet | VS Code Cheatsheet |
| 26 | Simple Machine Learning Cheatsheet | The Machine Learning Cheatsheet of all fields making it and common used algorithms | Machine Learning Cheatsheet |
| 27 | DeepMind & UCL on Reinforcement Learning | DeepMind & UCL lectures as videos on Reinforcement Learning | DeepMind & UCL on Reinforcement Learning |
| 28 | Stanford Machine Learning Full Course | Full machine Learning course as lecture slides given at Stanford University | Stanford Machine Learning Full Course |
| 29 |
