Tutorials on Ryan Orban

Machine Learning Mastery

me@ryanorban.com (Ryan Orban) — Mon, 07 Dec 2020 00:00:00 +0000

Summary

Machine Learning Mastery is Jason Brownlee’s blog and book series, one of the most visited machine learning sites on the internet. The approach is relentlessly practical: every post includes working Python code using standard libraries (scikit-learn, Keras, TensorFlow, statsmodels), and tutorials are organized around specific how-to questions (“How to implement LSTM time series forecasting in Python”, “How to tune hyperparameters with GridSearchCV”). The target audience is practitioners who want working implementations quickly.

150+ Best Machine Learning, NLP, and Python Tutorials

me@ryanorban.com (Ryan Orban) — Sun, 02 Aug 2020 00:00:00 +0000

Summary

Robbie Allen compiled this extensive list of machine learning, NLP, and Python tutorials on Medium, organized by topic. For 2020, it captured the best freely available learning resources across the ML stack — from beginner Python to advanced deep learning and NLP techniques.

20 Short Tutorials All Data Scientists Should Read and Practice

me@ryanorban.com (Ryan Orban) — Mon, 26 May 2014 00:00:00 +0000

Summary

This Data Science Central compilation serves as a curriculum map: 20 short tutorials that collectively cover the technical breadth expected of a working data scientist in 2014. The framing (should read and practice) is deliberate — these are hands-on exercises, not passive reading, with code examples in Python and R that readers can run and modify.

Learn Pandas — IPython Notebook Tutorial Series

me@ryanorban.com (Ryan Orban) — Fri, 02 May 2014 00:00:00 +0000

Summary

This Bitbucket repository by Hernán Rojas is a series of IPython notebooks for learning Pandas from scratch. In 2014, Pandas documentation was improving but still sparse on worked examples, and the library’s API was significantly different from what most people coming from R or Excel were used to. Tutorial series like this filled the gap.

How to Get Started with Machine Learning in Python

me@ryanorban.com (Ryan Orban) — Wed, 23 Apr 2014 00:00:00 +0000

Summary

This Prismatic story links to a tutorial on starting with machine learning in Python — covering the core libraries (Scikit-Learn, NumPy, Pandas) and basic workflow. In 2014, “how to get started with ML in Python” was a genuine question without a canonical answer: fast.ai didn’t exist yet, Coursera’s ML course used MATLAB, and the Python ML ecosystem lacked consolidated beginner resources.

The Flask Mega-Tutorial, Part III: Web Forms

me@ryanorban.com (Ryan Orban) — Tue, 22 Apr 2014 00:00:00 +0000

Summary

Miguel Grinberg’s Flask Mega-Tutorial was the go-to reference for learning Flask web development in the early 2010s. Part III covers web forms using Flask-WTF (a Flask extension wrapping WTForms), which handles form rendering, validation, and CSRF protection. This is the point in the tutorial series where a Flask project goes from returning static strings to handling user input — a meaningful threshold.

Statistical Data Mining Tutorials — AutonLab (CMU)

me@ryanorban.com (Ryan Orban) — Mon, 03 Mar 2014 00:00:00 +0000

Summary

The AutonLab at Carnegie Mellon University published this tutorial series on statistical data mining and machine learning as freely accessible PDFs — a significant resource in the early 2010s when most rigorous treatments were locked behind textbooks or paywalls. The lab, founded by Andrew Moore, focused on scalable algorithms for very large datasets, so the tutorials reflect both theoretical depth and computational practicality.

Codular — Web Development Tutorials

me@ryanorban.com (Ryan Orban) — Wed, 02 Jan 2013 00:00:00 +0000

Summary

Codular was an independent web development tutorial site active around 2012–2013, focused on practical guides for HTML, CSS, JavaScript, and PHP. The site published short, focused tutorials aimed at developers looking to learn specific techniques — typical content included CSS animations, jQuery plugins, PHP patterns, and responsive design techniques.