Name: Lei Duan
Type: User
Company: zynga
Bio: Hi, There!
My name is Lei, and finding stories hiding behind those data points, charts and models is my love.
Hope we all enjoy the journey of exploring! : )
Location: SF Bay Area
Blog: https://github.com/Lei-Duan
Lei Duan's Projects
this is a repo for storing my solutions to advent_of_code coding challenges
This is the presentation on - What are the key points one should consider if they will be appearing in Data Science job interview
深度学习入门教程&&优秀文章&&Deep Learning Tutorial
Collection of themes and tools for modifying ggplot2 plots
Building an image classifier using keras
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
A repository related to datasets for Machine Learning.
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.
This is a health care data competition using Machine learning model to predict impatient rate.
NLP analytics on billboard music lyrics
Practice your pandas skills!
This is a repo for my reading notes + reflections. technique + random topics.
This a coding script & report using Stepwise regression model to predict for a restaurant location choice based on both model performance and economical meaning behind parameters.
Here are some good resources to enhance your Data Driven Decisions
A game theoretic approach to explain the output of any machine learning model.
source:kaggle
quantitative trading with Javascript, Python, C++, Blockly, MyLanguage(麦语言)
This is a model selection coding script for predicting time series covering comparison between Lasso, PM and kitchen sink model as well as based on both MSE and economic loss function. The data is downloaded from Amit Goyal’s web site and is an extended version of the data used by Goyal and Welch (Review of Financial Studies, 2008). It contains monthly information on US stock returns as well as on a range of predictor variables proposed in the literature.
This is a work of visualizing the data of H1b sponsor from 2011 - 2016