azuracai

azuracai's Stars

• scutan90/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scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

  Language:JavaScript54.2k2.3k18815.8k

• halfrost/LeetCode-Go

  ✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解

  Language:Go32.7k633775.7k

• ageron/handson-ml2

  A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

  Language:Jupyter Notebook27.7k65651112.7k

• datasciencescoop/Data-Science--Cheat-Sheet

  Cheat Sheets

  Language:TeX18.3k

• 521xueweihan/git-tips

  :trollface:Git的奇技淫巧

  15.6k330303.2k

• mrdbourke/machine-learning-roadmap

  A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.

  7.5k356131.2k

• alteryx/featuretools

  An open source python library for automated feature engineering

  Language:Python7.2k1551k871

• rhiever/Data-Analysis-and-Machine-Learning-Projects

  Repository of teaching materials, code, and data for my data analysis and machine learning projects.

  Language:Jupyter Notebook6.1k336292.1k

• qiyuangong/leetcode

  Python & JAVA Solutions for Leetcode

  Language:Python5.2k123161.5k

• uber/causalml

  Uplift modeling and causal inference with machine learning algorithms

  Language:Python5k84393767

• alirezadir/Machine-Learning-Interviews

  This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

  Language:Jupyter Notebook4.3k755771

• facebookresearch/ReAgent

  A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)

  Language:Python3.6k148109516

• cdeweyx/DS-Career-Resources

  Compilation of resources for aspiring data scientists

  Language:Python1.9k580635

• iamtodor/data-science-interview-questions-and-answers

  Data science interview questions with answers. Not ideally (yet)

  1.6k362353

• combust/mleap

  MLeap: Deploy ML Pipelines to Production

  Language:Scala1.5k66472310

• practical-recommender-systems/moviegeek

  A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.

  Language:Python9015450361

• WillKoehrsen/hyperparameter-optimization

  Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms

  Language:Jupyter Notebook619206325

• khuyentran1401/awesome-Python-data-science-books

  Probably the best curated list of data science books in Python

  392190125

• longyinzaitian/MLInActionCode

  《机器学习实践》源码和《机器学习-算法原理与编程实践》源码以及学习心得

  Language:HTML229191164