Building a Recommender That Evolves with Seasons — One of the biggest challenges in the design of any recommender system (RecSys) is in handling temporal shifts. Since the world of fashion evolves with time, recommenders we design must adjust to the changing tides as well. In this article, we will consider how we can factor in the seasonal…

We will make use of transfer learning, approximate nearest neighbors, and embeddings centroid detection in PyTorch to build our recommender. — I have worked in the data industry for over seven years and had the privilege of designing, building, and deploying two recommender systems (RecSys) that went on to serve millions of customers. …

We will cluster COVID-19 X-ray images based on severity with our CNN RecSys flow using transfer learning, Spotify’s Annoy, and PyTorch — This work is meant as a proof-of-concept of how we can apply the same framework we set up in the previous CNN chapter onto a completely different domain. We will swap out the training data and employ a more powerful pre-trained model (Resnet152); the rest of the code remains identical…

We will build a recommender with transfer learning, Spotify’s Annoy, PyTorch, and return visually similar products across 240K images in 2ms — This is part of my Modern Visual RecSys series; feel free to check out the rest of the series at the end of the article. The Data We will be using a subset of DeepFashion data open-sourced by Liu Z. et al., The Chinese University of Hong Kong. Our data consists of…

In this chapter, we will explore the “hello world” data for visual models, the FashionMNIST dataset from Zalando with PyTorch, Tensorboard and Colab. — This is part of my Modern Visual RecSys series; feel free to check out the rest of the series at the end of the article. FashionMNIST and the visual challenge The data consists of: Training set of 60,000 images and a test set of 10,000 images. Each image is 28x28 grayscale, across 10 classes: T-shirt/top…

For this chapter, I will introduce the RecSys Design Framework with a case study of Amazon. — This is part of my Modern Visual RecSys series; feel free to check out the rest of the series at the end of the article. RecSys Framework — Amazon case study An eCommerce website like Amazon is heavily reliant on having a good RecSys. After all, users cannot be expected to browse through millions of products…

In this series of articles, I will introduce modern approaches to visual recommender systems. We begin with a case study of Spotify. — I have worked in the data industry for over seven years and had the privilege of designing, building, and deploying two recommender systems (RecSys) that went on to serve millions of customers. For each chapter, I will walk through case studies and share my experience designing RecSys.

I have the privilege of hosting Avi (VP — Data Sciences, AI & ML, InMobi), Hong Ting (CEO and Cofounder, Botbot.AI) and Kenny (Head of R&D Singapore, DataRobot) during the recent Tech in Asia Singapore 2018 conference. Here are the key takeaways. Q: What is AI and does the definition…