dabeardsadon Goto Github PK
Type: User
Type: User
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
课程视频、PPT和源代码:侯捷C++系列;台大郭彦甫MATLAB
《剑指Offer》第二版源代码
C++那些事
数据科学的笔记以及资料搜集
《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码
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18个章节,50余万字。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............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
📚 C/C++ 技术面试基础知识总结,包括语言、程序库、数据结构、算法、系统、网络、链接装载库等知识及面试经验、招聘、内推等信息。This repository is a summary of the basic knowledge of recruiting job seekers and beginners in the direction of C/C++ technology, including language, program library, data structure, algorithm, system, network, link loading library, interview experience, recruitment, recommendation, etc.
本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍,没准你想找的书就在这里呢,包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列(常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习,深度学习等等),大数据系列(Spark,Hadoop,Scala,kafka等),程序员必修系列(C、C++、java、数据结构、linux,设计模式、数据库等等)
Linux高性能服务器编程源码
:zap:机器学习实战(Python3):kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
Recommender Systems Paperlist that I am interested in
Recurrence the recommender paper with Tensorflow2.0
剖析 STL 是一种享受的过程!
tensorflow实战练习,包括强化学习、推荐系统、nlp等
项目描述
Windows程序设计(第5版 珍藏版)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.