Recommendation Systems & Text Analytics in Excel
Ratings matrices, cosine similarity, user- and item-based collaborative filtering, MAE against a popularity baseline, bag of words, TF-IDF and lexicon sentiment, built cell by cell for one online bookshop.
The first lesson is free — no account needed.
About this course
Build a recommendation system in Excel, and the text analytics behind it, cell by cell for one online bookshop. You read a user–item ratings matrix and its sparsity, measure cosine similarity between readers, predict ratings with user-based collaborative filtering, build a "customers who bought this also bought" box from item similarity, test the model against a popularity baseline with MAE, turn reviews into a bag of words, weight terms with TF-IDF and score sentiment with a word lexicon. No coding required, and the first lab is free.
Lessons
- The User–Item Ratings MatrixFree
- Cosine Similarity Between Users Pro
- User-Based Collaborative Filtering Pro
- Item-Based Similarity: "Customers Who Bought X" Pro
- Popularity Baseline & Evaluation with MAE Pro
- Bag of Words: Counting Words with Formulas Pro
- TF-IDF: Which Words Really Matter Pro
- Sentiment Scoring with a Word Lexicon Pro