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100-days-of-ml-code

100 Days of ML Coding

30-days-of-python

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.

chainknowledgegraph

ChainKnowledgeGraph, 产业链知识图谱包括A股上市公司、行业和产品共3类实体，包括上市公司所属行业关系、行业上级关系、产品上游原材料关系、产品下游产品关系、公司主营产品、产品小类共6大类。 上市公司4,654家，行业511个，产品95,559条、上游材料56,824条，上级行业480条，下游产品390条，产品小类52,937条，所属行业3,946条。

chatbot

fastapi-docker-tutorial

A tutorial of using the Docker encapsulation model API, Based on the FastAPI framework.

file-system

软件设计与开发实践Ⅱ(2015秋)

langchain-chatglm

langchain-ChatGLM, local knowledge based ChatGLM with langchain ｜ 基于本地知识库的 ChatGLM 问答

ml-for-beginners

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

oslab

HIT-CS 操作系统（2015秋）实验

playingchess

plm-nlp-code

python-algorithms

All Algorithms implemented in Python

selfkit

A small configuration toolkit, containing some tool software configuration information

software15

project of software engineering

umi-demo

wikipediacategorization

In this project we want to implement a solution that is capable of grouping Wikipedia articles based on the articles content or other features. We want to find feasible metrics to cluster articles into differentcategories. In the beginning we want to find very general categories e.g. science, politics, sports,movies, etc. and if possible, we want specify the categories into more detail, e.g. football player, actionmovie, midterm election, etc.. For this approach we want to use clustering.Possible extension: After we created a cluster we want to find a way to propose tags of related clustersfor a new article which is not in the cluster itself