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advanced-metrics-slides

Slide host for the advanced econometrics course for undergraduates

api

API Documentation

applied-methods-phd

Repo for Yale Applied Empirical Methods PHD Course

blm-replicate

Replication package for Bonhomme Lamadon and Manresa paper, A distributional framework for matched data

borusyak_lectures_ae

PhD Applied Econometrics class taught at UC Berkeley

causal-text-papers

Curated research at the intersection of causal inference and natural language processing.

cdlib

Community Discovery Library - (for networkx and igraph)

detext

DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks

detm

ding_causalinference_python

python implementation of Peng Ding's "First Course in Causal Inference"

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

dynetx

Dynamic Network Analysis library

emotion-classification-from-audio-files

Understanding emotions from audio files using neural networks and multiple datasets.

emotion-recognition-using-speech

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

financial-nlp

Constructing Financial Sentimental Factors in Chinese Market Using Techniques of Natural Language Processing

financialanalysisusingnlpandmachinelearning

Used text analytics (NLP) and machine learning to determine the true earnings quality of publicly listed companies

finbert

Financial Sentiment Analysis with BERT

food-reviews-sentiment-analysis

Sentiment analyzer that predicts the review star ( from 0 to 5, continuously) of given food text review.

gaminet

GAMI-Net: Generalized Additive Models with Structured Interactions

ggn

Gumbel Graph Network (GGN) : A General Deep Learning Framework for Network Reconstruction

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.

interpret

Fit interpretable models. Explain blackbox machine learning.

lectures

Lecture notes for EC 607

measuring-corporate-culture-using-machine-learning

Code Repository for MS20190155

nowak-price-smith-jrefe-2019

Creating real estate dictionaries using methods in Nowak, Price, Smith "Real estate dictionaries across space and time", Journal of Real Estate Finance and Economics, 2019

ojo_daps_mirror

The Open Jobs Observatory public mirror repo

openjobs-pin

openjobs_beta

Examples, code snippets and small packages for working with labour market data

predicting-first-impressions

Code and Data for "Predicting First Impressions with Deep Learning"

presidential_speeches

Text analysis of President Santos' speeches