Pak Shing Ho

Pak Shing Ho

Economist

Boston University

Biography

Pak Shing Ho is a Ph.D. candidate in Economics at Boston University. His research interests include macroeconomics, monetary and financial economics, and natural language processing (NLP).

Interests

  • Macroeconomics
  • Monetary and Financial Economics
  • Natural Language Processing (NLP)

Education

  • Ph.D., Economics, 2021

    Boston University

  • M.Res., Economics and Finance, 2015

    Universitat Pompeu Fabra (Barcelona GSE)

  • M.Sc., Economics, 2013

    London School of Economics and Political Science

  • B.Com., Economics, 2012

    The University of Melbourne

Skills

Python

90%

R

95%

Statistics

100%

Command Line

80%

Git

95%

Overleaf

100%

Experience

Professional

 
 
 
 
 

Economist

Amazon.com

May 2020 – Aug 2020 Seattle

Responsibilities include:

  • Economic Analysis
  • Econometric Modelling
  • Causal Inference and Event Studies
  • Time Series Forecasting
  • Statistical Package Development
  • Automation Design
 
 
 
 
 

Quantitative Researcher

Geode Capital Management

Jun 2019 – Aug 2019 Boston

Responsibilities include:

  • ESG Portfolio Construction and Back-testing
  • ESG Data Analysis
  • Statistical Modelling

Accomplish­ments

STATSX0001: Statistical Learning

edX Nov 2020 – Nov 2020
See certificate

DeepLearning.AI TensorFlow Developer Professional Specialization

Coursera Aug 2019 – Aug 2019
See certificate

Deep Learning Specialization

Coursera Jul 2019 – Jul 2019
See certificate

Machine Learning

Coursera Jun 2019 – Jun 2019
See certificate

Recent Posts

Resources for deep learning interviews

Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI https://arxiv.org/abs/2201.00650
Last updated on Tue, Jan 11, 2022 1 min read Deep Learning, Machine Learning

An overview of gradient descent optimization algorithms

The page written by Sebastian Ruder gives An overview of gradient descent optimization algorithms
Last updated on Tue, Oct 26, 2021 1 min read Machine Learning, ML

Reinforcement Learning Readings

Dissecting Reinforcement (Part 1 starts here) gives a very good intro to the subject using materials from Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig, and Reinforcement Learning: An Introduction by Richard S.
Last updated on Tue, Oct 26, 2021 1 min read Reinforcement Learning, Machine Learning, RL, ML

Understanding Decision Trees, Random Forests, Bagging and Boosting

Understanding Random Forests: From Theory to Practice https://arxiv.org/abs/1407.7502
Last updated on Sat, May 22, 2021 1 min read Machine Learning

Python Resources

Documentation Official Python 3 Documentation - “official” PEP 8 - Style Guide for Python Code Textbooks Dive Into Python survey of Python syntax, datatypes, etc. Think Python by Allen Downey - general overview of the Python language.
Last updated on Sat, Feb 27, 2021 2 min read Python
See all posts

Projects

Popular Topics

Deep Learning DL DSGE Finance Forecasting Machine Learning Macro ML Natural Language Processing NLP Python Reinforcement Learning RL RNN Text Mining Time Series Transformer

Contact

  • 270 Bay State Road, Boston, MA 02215
  • Enter School of Social Work (SSW) building from the east wing and take the stairs to Office B21 on the basement floor.
  • Office hours: online appointment only.
  • Book an appointment
  • LinkedIn
  • GitHub