Aprendizaje automático · GitHub

This is Andrew NG Coursera Handwritten Notes.

Aprendizaje automático rápido y preciso en 3 líneas de código

100 días de programación en aprendizaje automático

Convolutional neural network for analyzing pentest screenshots

Creo que los estudiantes de posgrado y quienes buscan empleo, a quienes va dirigido principalmente este libro, se beneficiarán de su lectura; no obstante, espero que también resulte fascinante para los investigadores más experimentados.

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.

🌟Más de 100 diagramas originales sobre los principios de LLM/RL📚, una gran obra del autor de *Algoritmos para modelos de lenguaje grandes*.💥 (Más de 100 mapas de algoritmos de 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: biblioteca de detección de puntos clave de múltiples personas en tiempo real para la estimación del cuerpo, el rostro, las manos y los pies

• 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 contiene figuras y plantillas que puedes reutilizar y personalizar para mejorar tu redacción científica.

ChatGPT资料汇总学习，持续更新......