Awesome resources - ML and Beyond

Exploring resources into Data science and Beyond. I share with you, some of the resources I considered during the last recent years, to learn data science and operations research, outside of my academic curriculum. 😎

Courses 📝

• Home | CS324 (stanford-cs324.github.io) - CS324 - Large Language Models
• Harvard CS197: AI Research Experiences - Dive into dev tools like Pytorch, and HF
• CS231n CNN for Visual Recognition - Stanford CS class
• ML & AI Courses | Google Cloud Training
• The Modern JavaScript Tutorial - Learn JavaScript
• airbnb/javascript: - JavaScript Style guide | GitHub

MLOps 🤖

• Effective MLOps with W&B (wandb.courses) - Effective MLOps: Model Development course
• Home - Made With ML - MLOps course
• Data Version Control · DVC - Apply version control to ML development.
• MLflow - A platform for managing the end-to-end ML lifecycle.

Deep learning 🕸

• Introduction to Probability Models - Sheldon M. Ross - Introduction to probability models.
• Discrete time Markov chains (bath.ac.uk) - a course on Markov chains.
• Differentiable neural computer - Wikipedia - memory augmented neural network architecture.
• https://udlbook.github.io/udlbook/ - Understanding Deep Learning notes.
• Understanding Deep Learning, by Simon J.D. Prince
• Speech and Language Processing (stanford.edu)
• Deep learning Cheat sheet - A summary of deep learning concepts shared by Stanford researchers.
• Learn TensorFlow and deep learning, without a Ph.D.
• TensorFlow tutorials
• google-research/tuning_playbook - A playbook for maximizing the performance of DL models.

Reinforcement Learning

• Gymnasium Documentation (farama.org) - OpenAI Gym agents.
• Proximal Policy Optimization (openai.com) - PPO algorithm, for the reinforcement learning.
• Bullet Real-Time Physics Simulation - Home of Bullet and PyBullet: physics simulation for games, visual effects, robotics and reinforcement learning.

LLM 💬

• 🦜🔗 LangChain - A framework for developing apps powered by language models.
• jerryjliu/llama_index - Provides an interface to connect your LLM’s with external data.
• Prompt engineering techniques - Azure OpenAI Service | Microsoft Learn.
• AutoTrain – Hugging Face 🤗 - Fine-tune Deep models with no code on Hugging Face.
• eugeneyan/open-llms - 🤖 A list of open LLMs available for commercial use.
• Significant-Gravitas/Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous.

AI Newsletter 📰

• The AiEdge Newsletter | Substack - Articles about MLOps.
• Blog - neptune.ai - Articles about applied ML, experiment tracking, and model registry.
• Lil’Log (lilianweng.github.io) - Personal blog from an OpenAI’s researcher.
• fast.ai - Making neural nets uncool again.
• Jay Alammar - Visualizing ML one concept at a time.

Operations research 🧩

• Operational Research, MC, IST - Learn the exact algorithms used in Linear Optimization.
• Real-time Scheduling Algorithms, MJC² - Resources on Scheduling algorithms applied to Supply chain.
• Optimization with PuLP - PuLP 2.7.0 documentation.
• OR-Tools  |  Google Developers - A fast and portable software for combinatorial optimization.
• Beer Game - Understand the effects of the bullwhip effect on Supply chain management.

Software dev 💻

• Developer Roadmaps - roadmap.sh
• jwasham/coding-interview-university - A complete CS study plan to become a software engineer.
• GeeksForGeeks - Learn CS and practice.
• FreeCodeCamp
• Corey Schafer - Youtube - Arguably the best YouTube channel for learning Python.
• TheAlgorithms/Python - All Algorithms implemented in Python.
• ossu/computer-science - Path to a free self-taught education in Computer Science!

Design 📐

• Modelling in Blender a Human Hand

Game Development 🕹️

• Learn how to make games with LÖVE - Tutorials on Game dev using Löve2D.
• Aseprite - Pixel art tool - Tool for drawing pixel art.
• GBA dev - Resources to start developing your GBA game.

Interactive programming 🔀

• Motion Canvas - Visualize Complex Ideas Programmatically.
• 3b1b/manim - Animation engine for explanatory math videos (Used by 3Brown1Blue).
• Typst - A productive alternative to $\text{LATEX}$ using Rust.

Books 📚

• Hands-On ML with Scikit-Learn, Keras, and Tensorflow
• Introduction to Statistical Learning, with R

Challenges

• LeetCode - Learn and prepare for technical interviews.
• Roadmap (neetcode.io) - Roadmap for practicing on LeetCode.
• Challenges | Inform - NASA Space Apps Challenge.

Good Read!

Relax