Apprentissage automatique · GitHub

100 jours de programmation en apprentissage automatique

Convolutional neural network for analyzing pentest screenshots

Je crois que les étudiants de troisième cycle et les personnes à la recherche d’un emploi, auxquels ce livre s’adresse principalement, tireront profit de sa lecture ; j’espère toutefois que même les chercheurs les plus expérimentés le trouveront également fascinant.

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

🌟The complete open-source release of the book 《 Deep Learning: Foundations and Concepts 》 and its related supporting resources

all kinds of text classification models and more with deep learning

The WeightWatcher tool for predicting the accuracy of Deep Neural Networks

Lightweight, powerful real-time speech translation with multilingual support and a multilingual UI.

• Local models: Run recognition models such as Qwen3-ASR and SenseVoiceSmall, and translation models such as HY-MT2 locally. The app can also search for and install other models from Hugging Face.
• Cloud models: Use speech recognition from Aliyun, MiniMax, and other providers; connect translation models through LLM protocols such as OpenAI-compatible APIs, Anthropic, or Ollama; or use the free MyMemory translation service.

Clean up noisy speech in real time with DPDFNet - open-source streaming speech enhancement for research, audio apps, and edge devices. Includes pretrained models, PyTorch code, ONNX/TFLite inference, 8/16/48 kHz support, and live demos.

🌟Plus de 100 schémas originaux sur les principes des LLM/RL📚, un ouvrage majeur de l’auteur de *Algorithmes pour les grands modèles de langage* !💥 (Plus de 100 cartes d’algorithmes LLM/RL)

ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

OpenPose : bibliothèque de détection en temps réel des points clés de plusieurs personnes, pour l’estimation du corps, du visage, des mains et des pieds

• 15, 18 or 25-keypoint body/foot keypoint estimation, including 6 foot keypoints. Runtime invariant to number of detected people.
• 2x21-keypoint hand keypoint estimation. Runtime depends on number of detected people. See OpenPose Training for a runtime invariant alternative.

Maia is a human-like neural network chess engine trained on millions of human games.

Automated deep learning algorithms implemented in PyTorch.

• NAS - TAS - Network Pruning via Transformable Architecture Search - NeurIPS-2019-TAS.md
• DARTS - DARTS: Differentiable Architecture Search - ICLR-2019-DARTS.md

🎨 ML Visuals contient des figures et des modèles que vous pouvez réutiliser et personnaliser pour améliorer votre rédaction scientifique.

ChatGPT资料汇总学习，持续更新......

100+ AI Machine learning Deep learning Computer vision NLP Projects with code

Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort

Tutoriel d’introduction aux systèmes de recommandation. À lire en ligne : https://datawhalechina.github.io/fun-rec/