Kay Huang's repositories
multi-factor-model-and-optimization
risk factor and several alpha factor in porfolio mgmt
deeplearning_ai_books
deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）
industry-machine-learning
A curated list of applied machine learning and data science notebooks and libraries across different industries.
supremebot_python
DIY supreme bot in python
2017-n2-Meetup
PREDICTIVE FINANCIAL ANALYTICS is about using statistical learning in Finance. Daniel Saxton uses GAM models to analyze cash flows, and Mark Bennett demonstrates how to predict security prices using corporate income statements.
artificial-intelligence-for-trading
Content for Udacity's AI in Trading NanoDegree.
DL.MonkeyMajik
Kay's solutions to Andrew Ng's deep learning course on Coursera
LeedCode_Solution
Kay's leetcode solution in Python
Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
CS_Offer
计算机学科基础知识和主流编程语言相关内容的总结
CtCI-6th-Edition-Python
Cracking the Coding Interview 6th Ed. Python Solutions
data_challenge_simulator
python script to simulate your own data challenge
Deep-Learning-21-Examples
《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码
deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
FreeML
Data Science Resources (Mostly Free)
gym-trading
Environment for reinforcement-learning algorithmic trading models
Kaggle-Mercari
32/2384 Solution to Kaggle Mercari Competition (solo silver medal winner)
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）
linearalgebra_refresher
kay's solution to linear algebra refresher course on udaciy
my-git
Individual collecting material of learning git（有关 git 的学习资料）
numpynet
Approachable neural net implementation in pure numpy
resample
Randomization-based inference in Python
Smart-beta-portfolio-optimization
dividend yield weighted index and minize portfolio variance
stanford-cs-230-deep-learning
VIP cheatsheets for Stanford's CS 230 Deep Learning
wtfpython
A collection of surprising Python snippets and lesser-known features.