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整理自然语言处理、推荐系统、搜索引擎等AI领域的入门笔记,论文学习笔记和面试资料(关于NLP那些你不知道的事、关于推荐系统那些你不知道的事、NLP百面百搭、推荐系统百面百搭、搜索引擎百面百搭)

repochat icon repochat

Chatbot assistant enabling GitHub repository interaction using LLMs with Retrieval Augmented Generation

reporeader icon reporeader

Explore and ask questions about a GitHub code repository using OpenAI's GPT.

ricky icon ricky

Want to be a freelance designer

rl-stock icon rl-stock

📈 如何用深度强化学习自动炒股

rlcard icon rlcard

Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

rpi icon rpi

【我是炬峰】视频里面用到的代码放在这里了。B站视频主页:https://space.bilibili.com/7848412

rssbot icon rssbot

Lightweight Telegram RSS notification bot. 用于消息通知的轻量级 Telegram RSS 机器人

segment-anything icon segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

selfreconcode icon selfreconcode

This repository contains a pytorch implementation of "SelfRecon: Self Reconstruction Your Digital Avatar from Monocular Video (CVPR 2022, Oral)".

simswap icon simswap

An arbitrary face-swapping framework on images and videos with one single trained model!

smplpix icon smplpix

SMPLpix: Neural Avatars from 3D Human Models

snowboy icon snowboy

Future versions with model training module will be maintained through a forked version here: https://github.com/seasalt-ai/snowboy

stock-tft icon stock-tft

Stock price prediction using a Temporal Fusion Transformer

stockprediction icon stockprediction

Hobby project in time series analysis with stock market data by comparing different methods for time series prediction, including ARIMA, SARIMAX, LSTM, and transformer.

stockpredictionai icon 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.

sttn icon sttn

paper : <Spatial-Temporal Transformer Networks for Traffic Flow Forecasting>

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