Material for gpu-mode lectures

Feature rich robust FastAPI template.

The simplest, fastest repository for training/finetuning medium-sized GPTs.

Acceptance rates for the major AI conferences

Contextual Doc Retrieval is a Python-based system leveraging OpenAI GPT-4o and Cohere for re-ranking and query expansion, combined with BM25 for accurate document retrieval. It parses PDFs, chunks …

A curated list of awesome responsible machine learning resources.

Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.

Seamlessly integrate LLMs as Python functions

Transcriptions of the seenunseen.in podcast generated using openai's whisper model

PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis

Python DDD example

An opinionated list of awesome Python frameworks, libraries, software and resources.

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing

🦉 Data Versioning and ML Experiments

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Distributed Asynchronous Hyperparameter Optimization in Python

Apache Spark - A unified analytics engine for large-scale data processing

A generative AI extension for JupyterLab

Convert Machine Learning Code Between Frameworks

🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

The fastai book, published as Jupyter Notebooks

The RedPajama-Data repository contains code for preparing large datasets for training large language models.

Algorithmic Trading in Python with Machine Learning

Clean PyTorch implementations of imitation and reward learning algorithms