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

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

https://github.com/imhuay/Algorithm_Interview_Notes-Chinese

 Tags interview machine-learning deep-learning algorithm chinese leetcode Implementation Python License Public Platform Windows Linux

LeetCode-Sol-Res - Clean, Understandable Solutions and Resources for LeetCode Online Judge Algorithm Problems

•    Java

This repository contains solutions and resources for LeetCode algorithm problems. An excel table for quick review before interview is also provided in resources directory.

algorithms_and_data_structures - 180+ Algorithm & Data Structure Problems using C++

•    C++

Note: Some of the code here is old and was written when I was learning C++. It might be possible that code is not safe or making wrong assumptions. Please use with caution. Pull requests are always welcome. Include contains single header implementation of data structures and some algorithms.

CS-Notes - :books: Computer Science Learning Notes

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:books: Computer Science Learning Notes

Evolutionary-Algorithm - Evolutionary Algorithm using Python

•    Python

In these tutorials, we will demonstrate and visualize algorithms like Genetic Algorithm, Evolution Strategy, NEAT etc. All methods mentioned below have their video and text tutorial in Chinese. Visit 莫烦 Python for more.

awesome-algorithm-question-solution - LeetCode，《剑指offer》中的算法题的题目和解法以及常见算法的实现

•    C++

LeetCode，《剑指offer》中的算法题的题目和解法以及常见算法的实现

Play-with-Algorithm-Interview - Codes of my MOOC Course <Play with Algorithm Interviews>

•    C++

Codes of my MOOC Course <Play with Algorithm Interviews>. Updated contents and practices are also included. 我在慕课网上的课程《玩儿转算法面试》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。

nndl - Another Chinese Translation of Neural Networks and Deep Learning

•    TeX

This is another (work in progress) Chinese translation of Michael Nielsen's Neural Networks and Deep Learning, originally my learning notes of this free online book. It's written in LaTeX for better look and cross-referencing of math equations and plots. And I borrowed some finished work from https://github.com/tigerneil/neural-networks-and-deep-learning-zh-cn. To compile the source code to a PDF file, please make sure you have a latest TeX system installed. You can download and install a TeX distribution for your platform from http://tug.org.

algorithm-exercise - Data Structure and Algorithm notes. 数据结构与算法/leetcode/lintcode题解/

•    Python

This work is some notes of learning and practicing data structures and algorithm. This project is hosted on https://github.com/billryan/algorithm-exercise and rendered by Gitbook. You can star the repository on the GitHub to keep track of updates. Another choice is to subscribe channel #github_commit via Slack https://ds-algo.slack.com/messages/github_commit/. RSS feed is under development.

machine-learning-for-software-engineers - A complete daily plan for studying to become a machine learning engineer

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Inspired by Google Interview University. This is my multi-month study plan for going from mobile developer (self-taught, no CS degree) to machine learning engineer.

awesome-scalability - Scalable, Available, Stable, Performant, and Intelligent System Design Patterns

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An updated and curated list of readings to illustrate best practices and patterns in building scalable, available, stable, performant, and intelligent large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users. Understand your problems: scalability problem (fast for a single user but slow under heavy load) or performance problem (slow for a single user) by reviewing some design principles and checking how scalability and performance problems are solved at tech companies. The section of intelligence are created for those who work with data and machine learning at big (data) and deep (learning) scale.

ML-From-Scratch - Machine Learning From Scratch

•    Python

Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible but rather to present the inner workings of them in a transparent and accessible way.

deepLearningBook-Notes - Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)

•    Jupyter

This content is part of a series following the chapter 2 on linear algebra from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. (2016). It aims to provide intuitions/drawings/python code on mathematical theories and is constructed as my understanding of these concepts. I'd like to introduce a series of blog posts and their corresponding Python Notebooks gathering notes on the Deep Learning Book from Ian Goodfellow, Yoshua Bengio, and Aaron Courville (2016). The aim of these notebooks is to help beginners/advanced beginners to grasp linear algebra concepts underlying deep learning and machine learning. Acquiring these skills can boost your ability to understand and apply various data science algorithms. In my opinion, it is one of the bedrock of machine learning, deep learning and data science.

awesome-algorithm - Leetcode 题解 (跟随思路一步一步撸出代码) 及经典算法实现

•    Python

If you are a newbie of Git, please check this tutorial we have made. Please note, this repository is inspired from KrisYu, and here is the approve letter. However, it has been modified, added and improved to reflect our knowledge, wisdom and efforts.

Reinforcement-learning-with-tensorflow - Simple Reinforcement learning tutorials

•    Python

In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years. If you speak Chinese, visit 莫烦 Python or my Youtube channel for more.

DeepLearningFlappyBird - Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).

•    Python

This project follows the description of the Deep Q Learning algorithm described in Playing Atari with Deep Reinforcement Learning [2] and shows that this learning algorithm can be further generalized to the notorious Flappy Bird. It is a convolutional neural network, trained with a variant of Q-learning, whose input is raw pixels and whose output is a value function estimating future rewards.

machine-learning-articles - Monthly Series - Top 10 Machine Learning Articles

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Click "Watch" to get an email notification once a month for Top 10 Machine Learning articles. Update will be made on major releases. Mybridge AI ranks articles by the number of shares, minutes read, and by its own machine learning algorithm.

keras-rl - Deep Reinforcement Learning for Keras.

•    Python

keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seamlessly integrates with the deep learning library Keras. Just like Keras, it works with either Theano or TensorFlow, which means that you can train your algorithm efficiently either on CPU or GPU. Furthermore, keras-rl works with OpenAI Gym out of the box. This means that evaluating and playing around with different algorithms is easy. Of course you can extend keras-rl according to your own needs. You can use built-in Keras callbacks and metrics or define your own. Even more so, it is easy to implement your own environments and even algorithms by simply extending some simple abstract classes. In a nutshell: keras-rl makes it really easy to run state-of-the-art deep reinforcement learning algorithms, uses Keras and thus Theano or TensorFlow and was built with OpenAI Gym in mind.

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