Awesome Data Analysis
Section: Resources · Resource for learning Bayesian methods in Python.
FreshScore 80
Entry
Bayesian Methods for Hackers
Appears in 5 awesome lists
by Cameron Davidson-Pilon. Introduction to Bayesian methods and probabilistic graphical models using tensorflow-probability (and, alternatively PyMC2/3).
Open github.comcamdavidsonpilon/probabilistic-programming-and-bayesian-methods-for-hackers
Found in these lists
Awesome Machine Learning
Section: Python · Book/iPython notebooks on Probabilistic Programming in Python.
FreshScore 93
Awesome Open Source Documents
Section: Data Science and Statistics · (Site, MIT) - An intro to Bayesian methods and probabilistic programming from a computation/understanding-first, mathematics-second point of view
FreshScore 85
Awesome TensorFlow
Section: Books · by Cameron Davidson-Pilon. Introduction to Bayesian methods and probabilistic graphical models using tensorflow-probability (and, alternatively PyMC2/3).
SlowScore 72
Machine Learning & Deep Learning Tutorials
Section: Bayesian Machine Learning
StaleScore 57
Often listed next to it
TensorFlow
How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs.
In 23 listsDetails
PyTorch
(label: good first issue) PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
In 16 listsDetails
Opik
Comet's open-source AI observability and evaluation platform: deep tracing of LLM calls, conversation logging, and agent activity, plus built-in eval metrics, prompt versioning, guardrails, and the Opik Agent Optimizer. Worth including because it unifies observability, verification, and…
In 16 listsDetails
transformers
(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…
In 14 listsDetails
Colossal-AI
(from Hpcaitech) - A Unified Deep Learning System for Large-Scale Parallel Training (1D, 2D, 2.5D, 3D and sequence parallelism, and ZeRO protocol).
In 14 listsDetails
Ray
A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. ray.io
In 13 listsDetails
Haystack
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search,…
In 13 listsDetails