luoyec Goto Github PK

ace592_luoye

[email protected]

auk

Working with eBird data in R

awesome-courses

:books: List of awesome university courses for learning Computer Science!

awesome-economics

A curated collection of links for economists

awesome-machine-learning-interpretability

A curated list of awesome machine learning interpretability resources.

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

bbs-forecasting

Research on forecasting using Breeding Bird Survey data

bulk-data-tools

Tools for working with USPTO bulk data product offerings.

c-lasso

The replication data and files for Liangjun Su, Zhentao Shi and Peter Phillips (2017, Econometrica): “Identifying Latent Structures in Panel Data”

causalinference

《基本有用的计量经济学》（MUSE）

columbia-ma-math-camp-2019

Hosting course material for Math Camp 2019 for the MA program at Columbia

cs446

CS446: Machine Learning in 2018 Spring, UIUC

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deepiv

Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction

dev-ii

Materials for The Graduate Center's Spring 2016 Economics Development II PhD seminar

eat_tensorflow2_in_30_days

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

egret

An R-package for the analysis of long-term changes in water quality and streamflow, including the water-quality method Weighted Regressions on Time, Discharge, and Season (WRTDS). http://usgs-r.github.io/EGRET/

enterprise-registration-data-of-chinese-mainland

**大陆 31 个省份1978 年至 2019 年一千多万工商企业注册信息，包含企业名称、注册地址、统一社会信用代码、地区、注册日期、经营范围、法人代表、注册资金、企业类型等详细资料。This repository is an dataset of over 10,000,000 enterprise registration data of 31 provinces in Chinese mainland from 1978 to 2019.【工商大数据】、【企业信息】、【enterprise registration data】。

geqfarm

Python module for general equilibrium farm size distribution in economies with and without market power distortions

gssurgo

Python package enabling an open source gSSURGO workflow

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.

info490-fa16

INFO 490: Foundations of Data Science, offered in the Fall 2016 Semester at the University of Illinois

info490-sp16

INFO 490: Advanced Data Science, offered in the Spring 2016 Semester at the University of Illinois

interpretable_machine_learning_with_python

Practical techniques for interpreting machine learning models.

ipen-5810

islr-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

jupyter_nbextensions_configurator

A jupyter notebook serverextension providing config interfaces for nbextensions.

linked-uspto-patent-data

matplotlib-cheatsheet

Matplotlib 3.1 cheat sheet. From an upcoming book on matplotlib.