firminayivodji Goto Github PK

anatomy

Shapley-based decomposition to anatomize the of out-of-sample accuracy of time-series forecasting models

applied-methods-phd

Repo for Yale Applied Empirical Methods PHD Course

applied_metrics

A PhD course in Applied Econometrics and Panel Data

assets

CV

awesome-explainable-ai

A collection of research materials on explainable AI/ML

bcf-workshop

Materials for the mini-course on deep learning and macro-finance.

bert_multimodal_transformer

blueprints-text

Jupyter notebooks for our O'Reilly book "Blueprints for Text Analysis Using Python"

books

Source code for 100+ books, kept here for quick reference

causal-inference

Causal Inference Mixtape Sessions

causal-ml-auto-inference

causal-text-papers

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

causalml-teaching

This repository consolidates my teaching material for "Causal Machine Learning".

cemfi-presession-2023

Pre-session materials for the 2023 Unstructured Data in Empirical Economics at CEMFI

centralbankroberta

CentralBankRoBERTA is a large language model. It combines an economic agent classifier that distinguishes five basic macroeconomic agents with a binary sentiment classifier that identifies the emotional content of sentences in central bank communications.

climate-macro-course

Course on 'Climate macroeconomics and finance' - University of Bologna

computational-data-analytics-for-economists

Computational Data Analytics for Economists

computational-methods-in-macro

PhD level course on advanved macro models dealing with agent heterogeneity.

computational-text-analysis-spring-2019

Computational text analysis for Spring 2019 by Caroline Le Pennec-Caldichoury

course-nlp

A Code-First Introduction to NLP course

course-text-data-2023

Materials for PhD/Master Course "Text Data in Business and Economics"

course-unstructured-data-23

Materials for the 2023 Unstructured Data in Empirical Economics course at CEMFI

crystal-ball-minimal-working-example

A MWE for the approach used in Byrne, Goodhead, McMahon, Parle (2022) and its companion paper.

deep-learning-in-r

Workshop (6 hours): Deep learning in R using Keras. Building & training deep nets, image classification, transfer learning, text analysis, visualization

deep-learning-with-python-notebooks

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

deepcca

An implementation of Deep Canonical Correlation Analysis (DCCA or Deep CCA) with pytorch.

deepequilibriumnets

deeplearning-books

detect-and-translate-text-data

How to detect language and translate text data into the language of your choice when working on a NLP project

did

Keeping track of what is going on with the latest DiD innovations.