I’m going to use NVTabular with PyTorch Lightning to train a wide and deep recommender model on MovieLens 25M. It’s quite a chimera implementation as you shall see.
NVIDIA Merlin is a high-level open-source library to accelerate recommender systems on NVIDIA GPUs at scale. I’m on a potato PC setup relying on free instances. Can I make it work?
Header image note: I typed ‘variation’ in Pexels and it popped up. Masarap! We can turn a simple autoencoder into something sophisticated. Autoencoders discover a latent mapping z, which as a lower-dimensional representation of the input x, can be useful for pre-training networks and creating recommender models. However, how autoencoders compress information may come in […]
Autoencoders are a simple neural network approach to recommendation
A tutorial to create a recommender pipeline with Kedro and MLFlow.
This is part 2 of my talk on recommenders. The presentation describes the intuitions of matrix factorization and how to implement it in R. I delivered this in the R-Users Group PH meetup group this November. If you wish to see some more recommender material in this blog, check this out:
Join me in this roadtrip of different recommender algorithms.
Hey all, it’s time for another machine learning blog. This time, I’m tackling recommendation systems. I’ve found this neat dataset, Steam Video games over at Kaggle. You should definitely check it out. We’ll be going from analyzing how people play these games, to how we can infer ratings from usage patterns. I’ll be implementing my […]