xtyawesome's starred repositories
Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
pytorch2keras
PyTorch to Keras model convertor
ml-mobileone
This repository contains the official implementation of the research paper, "An Improved One millisecond Mobile Backbone".
ghostnet_tf2
An implementation of GhostNet for Tensorflow 2.0+ (From the paper "GhostNet: More Features from Cheap Operations")
MobileOne-TF2
MobileOne backbone Tensorflow 2 implemention
Inpaint-Anything
Inpaint anything using Segment Anything and inpainting models.
digital_video_introduction
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
awesome-indie
Resources for independent developers to make money
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Prompt-Engineering-Guide
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
Deep-Learning-Interview-Book
深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）
audio_video_streaming
音视频流媒体权威资料整理，500+份文章，论文，视频，实践项目，协议，业界大神名单。
openvx-samples
OpenVX Samples to use with any conformant implementation of OpenVX
Khronosdotorg
Website resource pages for Khronos.org. Community is encouraged to help keep up-to-date
pytorch-ada
Another Domain Adaptation library, aimed at researchers.
transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
dann_tf2.0
DANN in TensorFlow 2.0
Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
Random-Erasing
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST
model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
interviews.ai
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.