Maschinelles Lernen · GitHub

Recommender Learning with Tensorflow2.x

Ein großartiges Projekt für die Hochschul-, Herbst- und Frühjahrsrekrutierung sowie für Praktika! Implementiere Schritt für Schritt eine leistungsfähige Deep-Learning-Inferenzbibliothek, die die Inferenz von Modellen wie llama2, Unet, Yolov5 und Resnet unterstützt.

An Open-sourced Knowledgable Large Language Model Framework.

Using modified BiSeNet for face parsing in PyTorch

Just draw a bounding box and you can remove the object you want to remove.

Collection of generative models in Pytorch version.

Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

Einfache Python-Implementierungen grundlegender Algorithmen des maschinellen Lernens

A comprehensive list of Implicit Representations and NeRF papers relating to Robotics/RL domain, including papers, codes, and related websites

Eine Machine-Learning-Aufgabe zur Bildreparatur, die Wasserzeichen intuitiv aus Bildern entfernt, sodass diese vom Ground-Truth-Bild nicht zu unterscheiden sind.

YoloV3 Implemented in Tensorflow 2.0

• yolov3 with pre-trained Weights
• yolov3-tiny with pre-trained Weights

This repository is no longer maintained.

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

• dynamic RNN(GRU, LSTM)
• Residual Network(Deep CNN)

A License Plate Image Reconstruction Project in Tensorflow2

The idea of this list is to collect shared data and algorithms around 3D Morphable Models. You are invited to contribute to this list by adding a pull request. The original list arised from the Dagstuhl seminar on 3D Morphable Models https://www.dagstuhl.de/19102 in March 2019.

This repo contains annotated research papers that I found really good and useful

Easy Docker setup for Stable Diffusion with user-friendly UI

A ResNet50-DCBAM deep learning framework for plant disease classification using the PlantVillage dataset with reproducible training and evaluation pipelines.

• ResNet50 backbone with pretrained ImageNet weights
• Channel attention

Massively Parallel Deep Reinforcement Learning. 🔥

A clean and readable Pytorch implementation of CycleGAN