Practical implementation of different Recommendation systems statergies
This was done as a part of the assesment for my masters
some parts of the code is borrowed from Prof Craig Macdonald
ReSys_1:
- MovieLens Data Exploration
- Popularity based Recommendation
- Association rules and Lift
ReSys_2:
- User based Colloborative Filtering
- Explicit Matrix Factorisation using Spotlight
- Latent Factors
- Popularity based Recommenders
- Implicit Recommendation
- BPR
ReSys_3:
- Explicit & Implicit Matrix Factorisation Models
- Hybrid Models
- Evaluating and Examining the Non-Personalised models
- Measuring Intra list diversity
- MMR Diversification