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谢伟浩's Projects

adain-style icon adain-style

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

awesome-cmake icon awesome-cmake

A curated list of awesome CMake scripts, modules, examples and others.

awesome-object-detection icon awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

awesome-recsys-papers icon awesome-recsys-papers

The awesome and classic papers in recommendation system!!! Good luck to every RecSys-learner!

awesome-rnn icon awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

best_ai_papers_2022 icon best_ai_papers_2022

A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.

book4_power-of-matrix icon book4_power-of-matrix

Book_4_《矩阵力量》 | 鸢尾花书:从加减乘除到机器学习;本册有,584幅图,81个代码文件,其中18个Streamlit App;状态:清华社五审五校中;Github稿件基本稳定,欢迎提意见,会及时修改

caffe icon caffe

Caffe: a fast open framework for deep learning.

caffe-model icon caffe-model

Caffe models (imagenet pretrain) and prototxt generator scripts for inception_v3 \ inception_v4 \ inception_resnet \ fractalnet \ resnext

cdae icon cdae

Collaborative Denoising Auto-Encoder for Top-N Recommender Systems

chatgpt-next-web-fork icon chatgpt-next-web-fork

一键拥有你自己的 ChatGPT 网页服务。 One-Click to deploy your own ChatGPT web UI.

chatgpt-on-wechat-fork icon chatgpt-on-wechat-fork

Wechat robot based on ChatGPT, which using OpenAI api and itchat library. 使用ChatGPT搭建微信聊天机器人,基于GPT3.5/4.0 API和itchat实现,能处理文本、语音和图片,访问操作系统和互联网。

crawler_samples icon crawler_samples

各种爬虫和大数据应用源码,可以直接在 神箭手云开发平台 上运行

cxxnet icon cxxnet

fast, concise, distributed deep learning framework

data-labeler icon data-labeler

Extracts object from raw images to train machine learning or deep learning models.

deeplearntoolbox icon deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

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