Maschinelles Lernen · GitHub

Convolutional neural network for analyzing pentest screenshots

Ich glaube, dass die Studierenden im Aufbaustudium und Arbeitssuchenden, an die sich dieses Buch in erster Linie richtet, von seiner Lektüre profitieren werden; dennoch hoffe ich, dass selbst die erfahrensten Forschenden es ebenfalls faszinierend finden werden.

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

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.

🌟Über 100 originale Schaubilder zu den Grundlagen von LLM/RL📚, ein bedeutendes Werk des Autors von *Algorithmen für große Sprachmodelle*!💥 (Über 100 LLM/RL-Algorithmusübersichten)

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

OpenPose: Echtzeitbibliothek zur Erkennung von Schlüsselpunkten mehrerer Personen für die Schätzung von Körper, Gesicht, Händen und Füßen

• 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 enthält Abbildungen und Vorlagen, die du wiederverwenden und anpassen kannst, um deine wissenschaftlichen Texte zu verbessern.

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

Einführung in Empfehlungssysteme. Online lesen: https://datawhalechina.github.io/fun-rec/

LLM algorithm practice lab with theory, solutions, and test cases.《大模型算法与系统教程》面向大模型入门到进阶的算法实战教程，覆盖原理讲解、答案解析、测试用例与 CUDA/Triton 实战。

• Notebook-first: Each lesson is organized around runnable code, exercises, answer cells, and basic validation.
• Goal-oriented entry: Start from Part 02 for implementation practice, or follow the architecture, post-training, inference, performance, and operator routes.

Ein Repository für Dokumenten-KI