This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!
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YOLOv6: a single-stage object detection framework dedicated to industrial applications.
Implement a reasoning LLM in PyTorch from scratch, step by step
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
- asr
- speaker-diarization
- speech
- speech-recognition
From the basics to slightly more interesting applications of Tensorflow
Tacotron 2 - PyTorch implementation with faster-than-realtime inference
Technical Analysis Library using Pandas and Numpy
- trading
- technical-analysis
- python3
- volume
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
- efficientdet
- efficientnet
- pytorch
- object-detection
Bonus materials, exercises, and example projects for our Python tutorials
Translated🎓 Academic portfolio that boosts citations. AI generates pages, you own as Markdown. BibTeX auto-import, Jupyter, LaTeX, slides, visual block editor — free to host forever. Academic homepage, AI-generated, Markdown-owned 👇
- hugo
- website-generation
- academic
- netlify
🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
- agent
- agentic
- agentic-ai
- agentic-rl
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
- machine-learning
- dockerfiles
- jetson
- pytorch
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
- machine-learning
- economics
- causal-inference
- causality
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
- bayesian-methods
- deep-learning
- machine-learning
- data-science
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
- reinforcement-learning
- machine-learning
- artificial-intelligence
- deep-reinforcement-learning
Data augmentation for NLP
- nlp
- augmentation
- machine-learning
- artificial-intelligence
Translated"PyTorch Practical Tutorial" (Second Edition): whether you are starting from zero, working on CV, NLP, or LLM project applications, or moving on to advanced engineering deployment, it's all here. We believe that with the help of this book, readers will be able to master the use of PyTorch with ease and become an excellent deep learning engineer.
- computer-vision
- deepsort
- diffusion-models
- onnx
The repository host gives no description.
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Python code for common Machine Learning Algorithms
- linear-regression
- polynomial-regression
- logistic-regression
- decision-trees
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
- tensorflow
- pytorch
- keras
- gobang
[ICCV 2019] Monocular depth estimation from a single image
- depth-estimation
- neural-network
- deep-learning
- self-supervision
Performance analysis of predictive (alpha) stock factors