anyang001,github

awesome-pytorch-list-cnversion

Awesome-pytorch-list 翻译工作进行中......

bag_of_tricks_for_image_classification_with_convolutional_neural_networks

experiments on Paper <Bag of Tricks for Image Classification with Convolutional Neural Networks> and other useful tricks to improve CNN acc

cheatsheets-ai

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

datalink

DataLink是一个满足各种异构数据源之间的实时增量同步、离线全量同步，分布式、可扩展的数据交换平台。

deep-learning-tricks

Enumerate diverse machine learning training tricks.

deepfacelab

DeepFaceLab is a tool that utilizes deep learning to recognize and swap faces in pictures and videos. Includes prebuilt ready to work standalone Windows 7,8,10 binary (look readme.md).

deepnude-an-image-to-image-technology

DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用GAN图像生成的理论与实践研究。

devilyuan

DevilYuan可视化股票量化系统，支持选股，历史数据自动下载，策略回测及参数优化，实盘交易和常用的统计功能

faceswap

Non official project based on original /r/Deepfakes thread. Many thanks to him!

finta

Common financial technical indicators implemented in Pandas.

ganhacks

starter from "How to Train a GAN?" at NIPS2016

jupyter-echarts

Bring echarts libraries to jupyter notebooks

jupyter-text2code

A proof-of-concept jupyter extension which converts english queries into relevant python code

mingpt

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

pulse

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

pyecharts

Python Echarts Plotting Library

quant-trading

Python quantitative trading strategies including Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD

spotmicro

Spot Micro Quadripeg Project

sstap-backup

收藏各版本SSTap程序以备不时之需

stockpredict

根据东财股吧爬虫数据进行自然语言分析，展示股市热度

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

ta-lib

Python wrapper for TA-Lib (http://ta-lib.org/).

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