fakedrug Goto Github PK

20_style-model-for-image-style-fusion-and-transfer

北京大学软件与微电子学院《人工智能实践》课程项目第6小组，新加入APP功能，项目代码持续完善中。

algo-zh

结构化算法刷题训练指南

algorithm-pattern

算法模板，最科学的刷题方式，最快速的刷题路径，你值得拥有~

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

astgcn-pytorch

cpt

This is the native Python implementation of CPT(compact Prediction Tree)

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

fakedrug.github.io

blogs

fast-neural-style-tensorflow

A tensorflow implementation for fast neural style!

helloworld

image-style-transfor

照片风格转换 项目主要参考Anish Athalye的Github项目 该项目是基于TensorFlow进行的视频图像转化，参考neural style这篇文章。

interview

Interview = 简历指南 + LeetCode + Kaggle

javaguide

【Java学习+面试指南】 一份涵盖大部分Java程序员所需要掌握的核心知识。

knn

机器学习实战

learn-with-open-source

借助开源项目，学习软件开发

leetcode

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

leetcode-1

LeetCode刷题记录与面试整理

leetcodeanimation

Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）

leetcodetop

汇总各大互联网公司容易考察的高频leetcode题🔥

lihang

Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]

lihang-code

《统计学习方法》的代码实现

machine-learning-in-action-python3

《机器学习实战》python3源码

pattern

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

pinche_xcx

同城拼车微信小程序:blush:

pinche_xcx_data

同城拼车微信小程序后端代码

pm4py-core

Public repository for the PM4Py (Process Mining for Python) project.

recsyspapers

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

rspapers

Must-read papers on Recommender System.

style_transfer

CNN image style transfer 🎨.

twitter-moods-as-stock-price-predictors-on-nasdaq

An attempt to predict next day's stock price movements using sentiments in tweets with cashtags. Six different ML algorithms were deployed (LogReg, KNN, SVM etc.). Main libraries used: Pandas & Numpy