THE LEARNING SHELF
A focused collection of official tutorials and documentation for learning AI, computer vision, and VR. Choose a small goal, work through one resource, and build something with what you learn.
01 / FOUNDATIONS
For readers who already understand basic programming and want to learn Python syntax, data structures, functions, and modules.
Write a function that reads a list of numbers and returns a useful summary.
02 / CORE CONCEPTS
A practical introduction to machine learning with explanations, visual examples, and exercises. Work through the prerequisites before starting.
Explain the difference between training, validation, and test data in your own words.
03 / FIRST MODELS
Use this after learning basic ML concepts. Explore model fitting, preprocessing, evaluation, and pipelines for working with structured data.
Build a simple baseline and compare its predictions with a held-out test set.
04 / COMPUTER VISION
Explore image processing before jumping straight into neural networks. Start with reading images, colour spaces, resizing, and simple transformations.
Load an image, resize it, convert it to grayscale, and save the result.
05 / DEEP LEARNING
Follow guided examples for tasks such as image classification. Start with an introductory tutorial and keep notes on the data, model, and evaluation.
Train a small classifier and inspect the examples it gets wrong.
05 / AN ALTERNATIVE
A walkthrough of tensors, datasets, models, training, and saving your work. It assumes familiarity with Python and basic deep learning concepts.
Reproduce the basic workflow and explain what happens in each training step.
06 / INTERACTIVE EXPERIENCES
A separate learning track for building VR experiences. Check the pathway prerequisites and hardware requirements before committing to a project.
Plan one small interaction: picking up an object, pressing a button, or moving through a space.
Need a starting point? Browse the project archive or read the guide to your first computer vision project.
These links point to external learning resources. They are not affiliate links. Providers may change their content, prerequisites, or access terms.