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Explain complex systems using visuals and simple terms. Help you prepare for system design interviews.
Literature references for “Designing Data-Intensive Applications”
📋 A list of open LLMs available for commercial use.
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
🦜🔗 Build context-aware reasoning applications
The simplest way to run LLaMA on your local machine
JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf
DeepDiff: Deep Difference and search of any Python object/data. DeepHash: Hash of any object based on its contents. Delta: Use deltas to reconstruct objects by adding deltas together.
VIP cheatsheets for Stanford's CS 229 Machine Learning
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
A playbook for systematically maximizing the performance of deep learning models.
🎓 Sharing machine learning course / lecture notes.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
Compilation of high-profile real-world examples of failed machine learning projects
Transforms PDF, Documents and Images into Enriched Structured Data
System design patterns for machine learning
RecTools - library to build Recommendation Systems easier and faster than ever before
Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains
List of awesome resources for machine learning-based algorithmic trading
Free MLOps course from DataTalks.Club