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ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

alphafold

Open source code for AlphaFold.

analysis-bacterium-temperature

android

no

android-demo-app

PyTorch android examples of usage in applications

androidknowledgesystem

The most complete Android advanced route knowledge map ⭐️你想要的最全 Android 进阶路线知识图谱+干货资料收集🚀

architecture-components-samples

Samples for Android Architecture Components.

battle-city

🎮 Battle city remake built with react.

bio-script

book_deeplearning_in_pytorch_source

c9-python-getting-started

Sample code for Channel 9 Python for Beginners course

chinese-chatbot-pytorch-implementation

:four_leaf_clover: Another Chinese chatbot implemented in PyTorch, which is the sub-module of intelligent work order processing robot. 👩‍🔧

classification-of-trash-using-neural-networks

The aim is to create a computer vision approach to classify garbage into recycling categories. This would be a very efficient way to process waste. The objective is to take images of a single piece of garbage and classify it according to its recyclability status. The multiclass classifier will be based on Convolutional Neural Networks.

coolweatherjetpack

酷欧天气的Jetpack版本实现，采用了MVVM架构。

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

csdn

data-science-notes

数据科学的笔记以及资料搜集

deep-learning-models

Keras code and weights files for popular deep learning models.

deep-learning-with-keras-notebooks

Jupyter notebooks for using & learning Keras

deeplearning-models

A collection of various deep learning architectures, models, and tips

dl-wastesort

基于深度学习的垃圾分类

esm

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

figma-handoff

A Figma handoff tool, support offline exporting.

foundations-for-analytics-with-python

garbage-classification-data

生活垃圾分类数据

garbage_calssify-by-resnet50-

使用迁移学习将resnet50用于垃圾分类，基于【华为云人工智能大赛·垃圾分类挑战杯】

garbage_classify

最严垃圾分类政策自7月1日颁布，如何进行垃圾分类已经成为居民生活的灵魂拷问。但是，没关系！AI在垃圾分类的应用可以成为居民的得力助手。本次垃圾分类挑战杯，目的在于构建基于深度学习技术的图像分类模型，实现垃圾图片类别的精准识别，大赛参考深圳垃圾分类标准，按可回收物、厨余垃圾、有害垃圾和其他垃圾四项分类。

git-tips

:trollface:Git的奇技淫巧

go-by-example