Maschinelles Lernen · GitHub

Offener Kurs für maschinelles Lernen

Fast, modular reference implementation and easy training of Semantic Segmentation algorithms in PyTorch.

• Modular Design: easily construct customized semantic segmentation models by combining different components.
• Distributed Training: >60% faster than the multi-thread parallel method(nn.DataParallel), we use the multi-processing parallel method.

Keras implementation of a CNN network for age and gender estimation

MobileNet build with Tensorflow

Fine-tune SAM (Segment Anything Model) for computer vision tasks such as semantic segmentation, matting, detection ... in specific scenarios

Einfache Python-Implementierungen grundlegender Algorithmen des maschinellen Lernens

A tensorflow implementation of EAST text detector

Ein Keras-Modell, das aus handgezeichneten Website-Mock-ups HTML-Code generiert. Es implementiert eine Bildbeschreibungsarchitektur für handgezeichnete Eingabebilder.

Single Shot MultiBox Detector in TensorFlow

A PyTorch implementation of the paper "All are Worth Words: A ViT Backbone for Diffusion Models".

Eine Stimme in 5 Sekunden klonen und beliebige Sprache in Echtzeit erzeugen

Hello AI World-Leitfaden zum Bereitstellen von Deep-Learning-Inferenznetzen und Deep-Vision-Primitiven mit TensorRT und NVIDIA Jetson.

Keras implementations of Generative Adversarial Networks.

🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.

A unified ecosystem and workspace for large-scale federated learning of Large Models & LLMS. Store compute as Wifi

Natural Language Processing Tutorial for Deep Learning Researchers

Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5