Code & Models
Some models from the book, as well as more advanced models, are available on github as a part of the TensorHouse project.
Chapter 3: Promotions and Advertisements
- Campaign/Channel Attribution using Adstock Model
- Customer Lifetime Value (LTV) Modeling using Markov Chain
- Next Best Action Model using Reinforcement Learning (Fitted Q Iteration)
- Multi-touch Multi-channel Attribution Model using Deep Learning (LSTM with Attention)
Chapter 4: Search
Chapter 5: Recommendations
- Nearest Neighbor User-based Collaborative Filtering
- Nearest Neighbor Item-based Collaborative Filtering
- Item2Vec Model using NLP Methods (word2vec)
- Customer2Vec Model using NLP Methods (doc2vec)
Chapter 6: Pricing and Assortment
- Markdown Price Optimization
- Dynamic Pricing using Thompson Sampling
- Dynamic Pricing with Limited Price Experimentation
- Price Optimization using Reinforcement Learning (DQN)
Extras: Supply Chain
