I've shared tons of free and inexpensive material for learning machine learning. Combined, their value is easily greater than a $145,092 machine learning degree. Here are the best ones:

Oops -- here's a link. Check it out! ai.stanford.edu/blog/learning-…

Learn how ReAct, a general paradigm for synergizing reasoning and acting in language models, presents more interpretable, diagnosable, and controllable task-solving trajectories while outperforming reasoning and acting only paradigms. Read the blog → goo.gle/3TiNcDp

What’s your favorite ML library and why?

A visual history of neural net research through diagrams from papers. Philipp was artist-in-residence in my NYU lab, funded by the Berggruen Foundation, when he started this project.

A Large Language Model trained on scientific papers. Type a text and galactica.ai will generate a paper with relevant references, formulas, and everything. Amazing work by @MetaAI / Papers with Code

MPCC Simulation environments in C++ and Matlab of the Model Predictive Contouring Controller (MPCC) for Autonomous Racing developed by the Automatic Control Lab (IfA) at ETH Zurich github.com/alexliniger/MP…

1/10: The summer break is the perfect time to share recent research from my lab. Our first story revolves around a fresh interpretation of diffusion-based generative modeling by my brilliant student Ying Fan. She proposed "diffusion models are solving a control problem".

We’re partnering with Uber to bring fully autonomous driving technology to even more people as we continue to scale. Later this year, Phoenicians will be able to use Waymo directly via the Uber app. 🤖🚘🏜️ blog.waymo.com/2023/05/waymo-…

Happy to share our latest #CoRL2024 paper, "Learning Transparent #Reward Models via Unsupervised Feature Selection". Gokhan Alcan Kevin Sebastian Luck Ville Kyrki Website: sites.google.com/view/transpare… #inversereinforcementlearning #rewardlearning #robotics #CoRL2024

Excited for the start of #CoRL. Does anyone know of any meetups or networking events not listed on the conference website? I know only this one. 1. Mujoco meetup - Friday 1-2pm

New paper by Joey Hong shows how we can train LLMs with value-based RL for multi-turn tasks *just by turning probabilities into Q-values*! This provides an algorithm that can be used for LLMs, VLMs, robotics tasks, etc. with one simple loss function. Thread👇