Whoeiy

Whoeiy's Stars

• varunexpsde/BigDataAnalytics

  Big data analytics repository, that includes the following projects: TF-IDF in Apache Hadoop & Decision Tree, SVD and Matrix Factorization in Apache Spark.

  Language:Jupyter Notebook1

• xiaoyugelaile/Music-Recommender-System

  基于协同过滤和SVD算法的音乐推荐系统

  Language:Jupyter Notebook397

• umangmehta12/netFlix_PrizeDataset

  Exploring the NetFlix Prize Dataset as final project for course CS6240 on Parallel Data Processing in MapReduce

  Language:Java11

• neeldani/Parallel-KNN

  A Parallel implementation of the famous K-Nearest-Neighborn (KNN) algorithm in CUDA as well as MPI

  Language:C9

• bsspirit/maven_hadoop_template

  Language:Java244265

• jadianes/spark-py-notebooks

  Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

  Language:Jupyter Notebook1.6k916

• ljcan/SparkStreaming

  Spark Streaming+Flume+Kafka+HBase+Hadoop+Zookeeper实现实时日志分析统计；SpringBoot+Echarts实现数据可视化展示

  Language:Java510258

• databricks/learning-spark

  Example code from Learning Spark book

  Language:Java3.9k2.4k

• twitter/elephant-bird

  Twitter's collection of LZO and Protocol Buffer-related Hadoop, Pig, Hive, and HBase code.

  Language:Java1.1k387

• tomwhite/hadoop-book

  Example source code accompanying O'Reilly's "Hadoop: The Definitive Guide" by Tom White

  Language:Makefile3.5k2.6k

• realguoshuai/hadoop_study

  定期更新Hadoop生态圈中常用大数据组件文档 重心依次为: Flink Solr Sparksql ES Scala Kafka Hbase/phoenix Redis Kerberos (项目包含hadoop思维导图 印象笔记 Scala版本简单demo 常用工具类 去敏后的train code 持续更新!!!)

  Language:Java925260

• SciML/SciMLBook

  Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

  Language:HTML1.9k336

• monklof/Back-End-Developer-Interview-Questions

  后端开发面试题，翻译自 https://github.com/arialdomartini/Back-End-Developer-Interview-Questions

  2.6k386

• arialdomartini/Back-End-Developer-Interview-Questions

  A list of back-end related questions you can be inspired from to interview potential candidates, test yourself or completely ignore

  15.5k1.9k

• niudai/How-to-be-a-good-programmer

  I'm here to tell you some amazing stuff which teacher would never tell you.

  Language:Makefile4.1k704

• caijc00/programmer_bookshelf_cn

  📚 一个程序员的书架

  Language:Python600376

• baomidou/dynamic-datasource

  dynamic datasource for springboot 多数据源 动态数据源 主从分离 读写分离 分布式事务

  Language:Java4.8k1.2k

• ityouknow/awesome-spring-boot

  Spring Boot Resources

  4.4k953

• hansonwang99/Spring-Boot-In-Action

  Spring Boot 系列实战合集

  Language:Java4.7k1.5k

• dyc87112/SpringBoot-Learning

  《Spring Boot基础教程》，2.x版本持续连载中！点击下方链接直达教程目录！

  Language:Java15.8k4.9k

• afatcoder/LeetcodeTop

  汇总各大互联网公司容易考察的高频leetcode题🔥

  18.8k2.7k

• MisterBooo/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）

  Language:Java75.6k14k

• geriskenderi/recommender-systems

  Implementations and evaluations of various recommender system algorithms and approaches

  Language:Jupyter Notebook51

• layer6ai-labs/RecSys2018

  1'st Place Approach by Layer6 AI to the 2018 ACM RecSys Challenge

  Language:Java8322

• jihoo-kim/RecSys-for-Playlist-Continuation

  State-of-the-art Papers & Codes on Recommender System for Playlist Continuation (2018~2020)

  9818

• JingzheSun/Recommender_System_Adaptive_KNN

  BPR recommender system

  Language:Python101

• gasevi/pyreclab

  pyRecLab is a library for quickly testing and prototyping of traditional recommender system methods, such as User KNN, Item KNN and FunkSVD Collaborative Filtering. It is developed and maintained by Gabriel Sepúlveda and Vicente Domínguez, advised by Prof. Denis Parra, all of them in Computer Science Department at PUC Chile, IA Lab and SocVis Lab.

  Language:C++12228

• vaexio/vaex

  Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

  Language:Python8.3k592

• yeomko22/ALS_implementation

  Implementation of ALS algorithm from "Collaborative Filtering for Implicit Feedback Data"

  Language:Jupyter Notebook433

• CSKrishna/Recommender-Systems-for-Implicit-Feedback-datasets

  Matrix Factorization augmented with customer item meta data

  Language:Jupyter Notebook228