机器学习、深度学习、自然语言处理等人工智能基础知识总结。

Overview

说明

机器学习、深度学习、自然语言处理基础知识总结。

目前主要参考李航老师的《统计学习方法》一书,也有一些内容例如XGBoost聚类深度学习相关内容NLP相关内容等是书中未提及的。

由于github的markdown解析器不支持latex,因此笔记部分需要在本地使用Typora才能正常浏览,也可以直接访问下面给出的博客链接。

Document文件夹下为笔记,Code文件夹下为代码,Data文件夹下为某些代码所使用的数据集,Image文件夹下为笔记部分所用到的图片。

由于时间和精力有限,部分代码来自github开源项目,如Seq2Seq、Transformer等部分的代码。

机器学习

深度学习

自然语言处理

待添加部分

  • 主题模型
  • LightGBM
Owner
Peter
一条渴望进步的咸鱼
Peter
A boosting-based Multiple Instance Learning (MIL) package that includes MIL-Boost and MCIL-Boost

A boosting-based Multiple Instance Learning (MIL) package that includes MIL-Boost and MCIL-Boost

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code for the ICLR'22 paper: On Robust Prefix-Tuning for Text Classification

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A flexible and extensible framework for gait recognition. You can focus on designing your own models and comparing with state-of-the-arts easily with the help of OpenGait.

Shiqi Yu 335 Dec 22, 2022
Code for paper 'Hand-Object Contact Consistency Reasoning for Human Grasps Generation' at ICCV 2021

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Hanwen Jiang 47 Dec 09, 2022
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Hand Distance Measurement Game This is program is made to calculate the distance

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Chunkmogrify: Real image inversion via Segments

Chunkmogrify: Real image inversion via Segments Teaser video with live editing sessions can be found here This code demonstrates the ideas discussed i

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Implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

SinGAN This is an unofficial implementation of SinGAN from someone who's been sitting right next to SinGAN's creator for almost five years. Please ref

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Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies

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