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120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

adversarial_autoencoder

A wizard's guide to Adversarial Autoencoders

aisenweibo

新浪微博第三方Android客户端

algorithmcode

Some Code for Algorithm

androidcustomview

自定义View

atomix

A reactive Java framework for building fault-tolerant distributed systems

awesome-human-pose-estimation

A collection of awesome resources in Human Pose estimation.

caml

cmt

cnn_depth_tensorflow

depth estimation using tensorflow

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

deepgamingai_fifarl

Using Reinforcement Learning to play FIFA

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为15个章节，近20万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 版权所有，违权必究 Tan 2018.06

deeppose

DeepPose implementation in Chainer

deeppose_tf

DeepPose implementation on TensorFlow. Original Paper http://arxiv.org/abs/1312.4659

dkn

A tensorflow implementation of DKN (Deep Knowledge-aware Network for News Recommendation)

flask

The Python micro framework for building web applications.

flask-examples

Code for my "Python Web Development with Flask" presentation.

flask-vue-crud

Single Page App with Flask and Vue.js

flask-vuejs-survey

Code for Tutorial Blog Series

gbt

geo-cluster

Geographic KMeans clustering in Groovy/Java

geo-data-viewer

🗺️ Geo Data Viewer w/0 Py 🐍 || pyWidgets ⚙️ || pandas 🐼 || @reactjs ⚛️ required to gen. some snazzy maps 🗺️ with keplerGL ...

gt-nlp-class

Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"

haversine

Small Java class for calculating the distance between two points.

implicit

Fast Python Collaborative Filtering for Implicit Feedback Datasets

interview_notes-chinese

2018/2019/校招/春招/秋招/自然语言处理(NLP)/深度学习(Deep Learning)/机器学习(Machine Learning)/C/C++/Python/面试笔记

jeecg-boot

一款基于代码生成器的JAVA快速开发平台，开源界“小普元”超越传统商业企业级开发平台！采用前后端分离架构：SpringBoot 2.x，Ant Design&Vue，Mybatis-plus，Shiro，JWT。强大的代码生成器让前后端代码一键生成，无需写任何代码! 引领新的开发模式(OnlineCoding模式-> 代码生成器模式-> 手工MERGE智能开发)，帮助Java项目解决70%的重复工作，让开发更多关注业务逻辑。既能快速提高开发效率，帮助公司节省成本，同时又不失灵活性。JeecgBoot还独创在线开发模式（No代码）：在线表单配置（表单设计器）、移动配置能力、在线工作流配置（流程设计器）、在线报表配置、在线图表配置、插件能力（可插拔）等等

jump

leetcode-oj-java-solution

My Solutions for Leetcode OJ in Java