https://github.com/davidchocholaty/machine-learning-resources

A Journey through Machine Learning
https://github.com/davidchocholaty/machine-learning-resources

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A Journey through Machine Learning

• Host: GitHub
• URL: https://github.com/davidchocholaty/machine-learning-resources
• Owner: davidchocholaty
• Created: 2023-07-10T16:16:25.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-02-12T20:50:21.000Z (9 months ago)
• Last Synced: 2024-02-12T21:53:32.576Z (9 months ago)
• Size: 1000 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# A Journey through Machine Learning

A repository containing mostly free resources that I find useful for my machine learning studies.

## 2023

##### Artificial Intelligence: A Modern Approach (book)

https://people.engr.tamu.edu/guni/csce421/files/AI_Russell_Norvig.pdf

*One of the most classic books on machine learning and artificial intelligence, covering topics such as search algorithms, constraint satisfaction problems (CSPs), Bayesian networks, and more.*

##### Neural Networks: Zero to Hero

https://www.youtube.com/watch?v=VMj-3S1tku0&list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ

*IMHO the first video is the best explanation of the neural networks basics that I have found, I surely recommend.*

##### Neural Networks (book)

http://www.dkriesel.com/en/science/neural_networks

*Used in the Soft Computing course at BUT FIT. Not recommended for beginners, but it provides a nice cross-section of various general neural network types.*

## 2024

##### Machine Learning Crash Course

https://developers.google.com/machine-learning/crash-course

*In my opinion, this is an awesome introductory guide, also friendly for beginners. It covers the most important parts of machine learning that are taught in the university courses I graduated from as well.*

##### Deep Learning (book)

https://www.deeplearningbook.org/

*I believe this is one of the most famous deep learning books, so no further comment is needed.*

##### Reinforcement Learning: An Introduction (book)

https://www.andrew.cmu.edu/course/10-703/textbook/BartoSutton.pdf

*One of the best books on reinforcement learning.*

##### Clean Code (book)

https://github.com/jnguyen095/clean-code/blob/master/Clean.Code.A.Handbook.of.Agile.Software.Craftsmanship.pdf

*Just needed.*

##### Machine Learning, Data Science and Generative AI with Python

https://www.udemy.com/course/data-science-and-machine-learning-with-python-hands-on/?couponCode=24T1MT101824

*An awesome course that covers the most important parts, starting with the basics and progressing to more advanced topics.*

##### Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT

https://www.udemy.com/course/artificial-intelligence-az/

*A-Z course.*

##### ChatGPT, Midjourney, DALL-E 3 & APIs - The Complete Guide

https://www.udemy.com/course/chatgpt-bard-bing-complete-guide-to-chatgpt-openai-apis/?couponCode=24T1MT101824

*Great for tools like ChatGPT, etc.*

##### ChatGPT Prompt Engineering for Developers

https://learn.deeplearning.ai/courses/chatgpt-prompt-eng/lesson/1/introduction

*For prompt engineering.*

##### Lil’Log

https://lilianweng.github.io/

Lilian Weng's blog covers advanced topics on ML and LLMs—love it!