Data Science
This page contains links to my Colab/Jupyter notebooks, as well as useful paid and free online resources. Also, see my GitHub Repo here: https://github.com/DataHurdler/UdemyPracticeCode.
Project Notebooks
Simple TF-IDF Movie Recommender
Link to Google Colab Notebook
This is an exercise from Section 2 of Udemy’s Machine Learning: Natural Language Processing in Python by the Lazy Programmer. The exercise builds a movie recommender with ONLY TF-IDF (no learning).
Time Series Analysis of Movie Sales in Shanghai
Link to Google Colab Notebook
I analyze movie sales in Shanghai from 2012-2015 with exponential smoothing (from statsmodels) and Facebook’s Prophet. The data is reduced from the one used in my research paper “The impact of air pollution on movie theater admissions”.
Online Resources
YouTube
Coursera/Udemy Courses
Datasets
Books
- Causal Inference: The Mixtape Link
- Discrete Choice Methods with Simulation Link
- Forecasting: Principles and Practice Link
- An Introduction to Statistical Learning Link
- Deep Learning Link
- Introduction to Probability for Data Science Link
- Scientific Visualization: Python + Matplotlib Link
- Reinforcement Learning: An Introduction Link
- R for Data Science (2e) Link
Web Sites/Pages
- Comprehensive list of activation functions in neural networks with pros/cons Link