Name: Edgar Akopyan
Type: User
Company: Ludwig Maximilians Universität
Bio: Masters in Quantitative Economics at the University of Munich. Graduate of Philosophy, Politics and Economics at the London School of Economics.
Location: Munich, Germany
Edgar Akopyan's Projects
The Armenian survey data is in CSPro format. This is a code that transforms it into an R compatible dataset.
Code for "Assessment of Machine Learning models in Economic Research" Master Thesis.
:book: A curated list of resources dedicated to Natural Language Processing (NLP)
The 3rd edition of course.fast.ai
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.
Second Website
Personal Website
The fastai deep learning library, plus lessons and tutorials
Generalized Random Forests
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.
MY personal repo for ICML2021 talks and papers
Lecture notes for EC 607
The code transforms LEI Dataset of Commercial legal entities and their relations into csv files. (to be updated)
Literature for the self-taught AI practitioner! 📚
Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading
This is a code for scraping map of mass burials during the Spanish Civil War. The information on locations is taken from Spanish Government website.
This is a repository of code and data for a paper studying unfair inequality in Russia. More information available in the READ.ME file.
Машинное обучение на ФКН ВШЭ
DL course co-developed by YSDA, HSE and Skoltech
(JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
My attempt at https://www.kaggle.com/c/tabular-playground-series-apr-2021/data
A depository with a code for my team undergraduate statistics paper, analysing Zomato Restaurant dataset from Kaggle.