Tutorials¶
Step-by-step tutorials for building complete applications with HoloVec.
These tutorials walk you through real-world applications from start to finish, showing you how to combine models, encoders, and techniques to solve practical problems.
Tutorial Overview¶
Each tutorial includes:
Complete working code - Copy and run immediately
Step-by-step explanations - Understand every decision
Best practices - Learn optimal patterns
Extensions - Ideas for going further
Available Tutorials¶
Text Classification¶
Tutorial: Text Classification - Build a complete text classifier from scratch
What you’ll learn:
Encoding text with n-grams
Training with example documents
Classifying new text
Evaluating accuracy
Optimizing performance
Time: 20-30 minutes
Prerequisites: Basic Python, understanding of text classification
Recommender System¶
Tutorial: Building a Recommender System - Create a content-based recommendation engine
What you’ll learn:
Encoding multi-feature items (price, category, ratings)
Building product representations
Finding similar items
Implementing collaborative filtering patterns
Scaling to large catalogs
Time: 20-30 minutes
Prerequisites: Basic Python, familiarity with recommendation systems
Next Steps¶
After completing these tutorials:
Explore HoloVec Examples - 28 focused examples
Read User Guide - In-depth guides for models, encoders, backends
Check API Reference - Complete API reference
See Also¶
Quickstart - Quick introduction to HoloVec
Choosing a VSA Model - Choose the right VSA model
Encoding Data - Encode different data types
HoloVec Examples - Focused code examples