// the find
rhiever/Data-Analysis-and-Machine-Learning-Projects
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
A collection of standalone Jupyter notebooks by Randal Olson, each tied to a blog post — TSP-based road trip optimization, TPOT AutoML demos, vaccine visualization, Twitter follower analysis, and a handful of others. It's teaching material, not a library. Useful for people learning how to apply algorithms to real-world messy data, less useful if you want something to build on.
The road trip and TSP notebooks are genuinely well-constructed — they show the full pipeline from distance matrix to genetic algorithm output, not just the happy-path sklearn fit/predict. The TPOT demo is a clean entry point to automated pipeline search before AutoML became overcrowded. Data is included in the repo so notebooks actually run without hunting down datasets. License split (CC-BY for content, MIT for code) is thoughtfully done for teaching material.
Badged for Python 2.7 and 3.5 — this is 2016-era code and it shows; many notebooks will break against current pandas and matplotlib without manual fixes. Dead since 2023 and no sign of maintenance. The collection is shallow: 10 standalone projects with no shared utilities, no common structure, and no way to tell which notebooks still work. The Twitter follower notebook references an API that no longer exists in its original form.