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21 Lessons, Get Started Building with Generative AI
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
A latent text-to-image diffusion model
Examples and guides for using the OpenAI API
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
A game theoretic approach to explain the output of any machine learning model.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
A High-Quality Real Time Upscaler for Anime Video
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
Kubernetes community content
AirLLM 70B inference with single 4GB GPU
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
A collection of infrastructure and tools for research in neural network interpretability.
A crash course in six episodes for software developers who want to become machine learning practitioners.
0xSojalSec / airllm
Forked from lyogavin/airllmAirLLM 70B inference with single 4GB GPU
Statistics Tutorial for IT Operations Engineers
Este repositório não está recebendo atualizações | A platform for profiling public figures in Brazilian politics
Códigos usados no Curso de Análise de Dados Públicos usando Programação (python), oferecido online por meio do canal do Youtube do LabHackerCD (Assistam -> https://www.youtube.com/playlist?list=PLq…
Catalog of profilers, profile data formats, data format converters, and profile analysis UIs.
"Network/Graph Analysis in Python" repository of 3 hours training session held at ODSC East 2018 and JupyterCon 2018.
using pandas to analyze data from brazilian federal senate