Alexyskoutnev's Stars
jlevy/the-art-of-command-line
Master the command line, in one page
bregman-arie/devops-exercises
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
facebookresearch/segment-anything
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.
mingrammer/diagrams
:art: Diagram as Code for prototyping cloud system architectures
astral-sh/ruff
An extremely fast Python linter and code formatter, written in Rust.
Asabeneh/30-Days-Of-React
30 Days of React challenge is a step by step guide to learn React in 30 days. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
facebookresearch/fastText
Library for fast text representation and classification.
microsoft/graphrag
A modular graph-based Retrieval-Augmented Generation (RAG) system
stanfordnlp/dspy
DSPy: The framework for programming—not prompting—language models
ItzCrazyKns/Perplexica
Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI
dexteryy/spellbook-of-modern-webdev
A Big Picture, Thesaurus, and Taxonomy of Modern JavaScript Web Development
google/yapf
A formatter for Python files
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
jacobgil/pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Mooler0410/LLMsPracticalGuide
A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)
Unstructured-IO/unstructured
Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
NVIDIA/TensorRT-LLM
TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.
anthropics/anthropic-cookbook
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
CASIA-IVA-Lab/FastSAM
Fast Segment Anything
adam-maj/tiny-gpu
A minimal GPU design in Verilog to learn how GPUs work from the ground up
pytorch/serve
Serve, optimize and scale PyTorch models in production
MaartenGr/KeyBERT
Minimal keyword extraction with BERT
rail-berkeley/rlkit
Collection of reinforcement learning algorithms
LIANGKE23/Awesome-Knowledge-Graph-Reasoning
AKGR: Awesome Knowledge Graph Reasoning is a collection of knowledge graph reasoning works, including papers, codes and datasets
neo4j/neo4j-python-driver
Neo4j Bolt driver for Python
shariqiqbal2810/maddpg-pytorch
PyTorch Implementation of MADDPG (Lowe et. al. 2017)
texttron/hyde
HyDE: Precise Zero-Shot Dense Retrieval without Relevance Labels
facebookresearch/BenchMARL
A collection of MARL benchmarks based on TorchRL
kiwi-sherbet/PRESTO
Official codebase for PRESTO (Planning with Environment Representation, Sampling, and Trajectory Optimization)
npotteig/rust_thetastar
A 2.5D ThetaStar Algorithm in Rust with Python Bindings