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Welcome
Getting Started
Why Python and finance?
Python set-up
Using Github and Github Codespaces
Markdown
Packages
Code style, PEP8, and linting
AI Coding Assistants
The Basics
CompSci 101: Types, control, and numpy arrays
The Basics
Numpy and arrays
Working with data
Importing data
pandas
Cleaning our data
Exploratory data analysis (EDA)
Merging and reshaping data
Using SQL in Python
polars: A fast, fancy pandas alternative
Data visualization
seaborn
matplotlib
plotly
Data APIs
FRED API
NASDAQ Data Link
Databento
WRDS (Wharton Research Data Services)
Financial time series
Applications
Essential portfolio math
Portfolio optimization
Machine learning and unsupervised learning
Factor models
Regression and supervised machine learning
OLS regression in Python
Regularization: Ridge, Lasso, and Elastic Net
The machine learning workflow with sklearn
From Regression to Prediction: Can ML Beat the Market?
Logit models
Risk management
Monte Carlo and portfolios
Decision Trees
Option basics
Trading strategies and backtesting
Backtesting with the BT Package
Factor Analysis with Alphalens
Textual Analysis in Finance
How Large Language Models Work
.ipynb
.pdf
Decision Trees
Decision Trees
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