47,133 repositories indexed
1–19 of 19 · Most stars
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
High-Resolution Image Synthesis with Latent Diffusion Models
TranslatedLangGPT: Empowering everyone to become a prompt expert! 🚀 📌 Proposer of Structured Prompt 📌 Initiator of Meta-Prompt 📌 The most popular paradigm for putting prompts into practice | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树 (Yunzhong Jiangshu, "river and trees amid the clouds")
Flax is a neural network library for JAX that is designed for flexibility.
Bayesian optimization in PyTorch
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
Complex code hides connections, workflows, and business risks.Unvibe complex code. Trace business workflows.
TeachOpenCADD: a teaching platform for computer-aided drug design (CADD) using open source packages and data
Python package for Bayesian Machine Learning with scikit-learn API
bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.
Deep Reinforcement Learning for de-novo Drug Design
Optimising chemical reactions using machine learning
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
A coding exercise: let's convert dirty machine learning code into clean code using a Pipeline - which is the Pipe and Filter Design Pattern applied to Machine Learning.
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.