Name: Mustapha Mohammed, PhD
Type: User
Company: London
Bio: Research Fellow | Statistician with interest in
Spatial Econometrics, Macroeconometrics, Bayesian Statistics, Health Econometrics and Medical Statistics
Location: England, UK
Mustapha Mohammed, PhD's Projects
Course materials associated with the 2022 LTCC course on Functional Data Analysis
Interactive tutorial on the Forward-Backward Expectation Maximization algorithm
Compiled lab materials for ESM 206 (Fall 2019)
VAR and FAVAR models in R for 8th semester project
Computational data tools for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
Textual analysis of FOMC Transcripts. My research examines the relationship between words said during FOMC meetings, and changes in Federal Funds Rate. You can walk through my data cleaning, processing, and analysis process here.
Material for the course on machine-learning based environmental monitoring at geostat 2018
simple and scalable statistical modelling in R
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.
Notebooks and code for the book "Introduction to Machine Learning with Python"
Houses IPA's Stata training courses and code.
International Trade Network Analysis in R. This package can clean and transform international trade data from WITS (http://wits.worldbank.org/) into a international trade network and undertake descriptive analysis
Run IV/2SLS with many levels of fixed effects (i.e. ivreg2+reghdfe)
simple tools for data cleaning in R
Collections of Tutorials and Demos for Learning Julia in Data Science and Computing
Jupyter metapackage for installation, docs and chat
Lectures on dynamic programming at Keio University
Lecture notes for EC 607
Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay
An introduction to Machine Learning Algorithms and code
An implementation of a complete machine learning solution in Python on a real-world dataset. This project is meant to demonstrate how all the steps of a machine learning pipeline come together to solve a problem!
This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation
A collection of machine learning examples and tutorials.
Course Website on Macroeconomic Analysis with Machine Learning and Big Data
Macroeconomics with Python
Mastering Machine Learning with R, Third edition, by Packt
This is a 2nd Year PhD Course In Micro-econometrics