Microstrong0305

Python2AI

从零开始学习人工智能

WeChat-zhihu-csdnblog-code

WeChat Official Accounts, zhihu and CSDN'blog code

Screenshot-to-Code

Generating Code from a Graphical User Interface Screenshot

Chinese-Spark-movie-lens

基于Spark、Python Flask和MovieLens dataset的在线电影推荐系统

Recommendation_System_practice

记录学习推荐系统的demo

GNN_Review

GNN综述阅读报告

awesome-vpn

Free VPN/proxy,server,account,link list.,实时更新免费的代理,科学上网,翻墙,梯子,服务器,客户端,账号

CTR

CTR模型代码和学习笔记总结

GNNPapers

Must-read papers on graph neural networks (GNN)

interview-algorithm-python

从一个算法工程师的角度，总结实习/校招/社招中遇到的考察编程能力的题目，不限于《剑指offer》、Leetcode等等。

ngender

根据姓名来判断性别

PLMpapers

Must-read Papers on pre-trained language models.

BERT4Rec

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

implicit

Fast Python Collaborative Filtering for Implicit Feedback Datasets

NLP

one-key-hidpi

Enable macOS HiDPI and have a native setting.

RecVAE

The official PyTorch implementation of the paper "RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback"

spotlight

Deep recommender models using PyTorch.

transformers

🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

TurboTransformers

a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU.

xlearn

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

coding_interviews

《剑指Offer》题目汇总&常考题总结(Python实现)

competition-baseline

数据科学竞赛各种baseline代码、思路分享

fun-rec

推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/

leetcode-master

《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀

pylift

Uplift modeling package.

RecommenderSystem

thundergbm

ThunderGBM: Fast GBDTs and Random Forests on GPUs

tips_for_interview

Some of my thoughts about interview. 我的一些面试心得