This blog is based on a hack week I did near the end of 2020. For background, the ShopRunner Data Science allows members to spend a week per quarter working on a ShopRunner-related topic of their choice. Ever since getting involved in e-commerce data science, one of the things I…

When not blogging about data science, I work as a Senior Data Scientist at an e-commerce company called ShopRunner. Over the past year, our team has been building out large multi-task deep learning ensembles to predict relevant fashion attributes and characteristics of products within our product catalog using both images…

Co-written by Nicole Carlson and Michael Sugimura — NOTE: Our team previously had a tradition of naming projects with terms or characters from the Harry Potter series, but we are disappointed by J.K. Rowling’s persistent transphobic comments. In response, we renamed the Tonks Library as Octopod. More details on that process here. Intro Nicole Carlson and Michael Sugimura are…

In my first Pendragon Four blog I introduced my multi-agent reinforcement learning (RL) setup for the mobile phone game Fate Grand Order (FGO) I listed a few goals: 1) Add supports to the game FGO does not have a player vs player aspect and basically all the characters are viable…

Over the past year I have made various versions of neural network powered bots to play the game Fate Grand Order (FGO), loosely called Project Pendragon. The work around Project Pendragon ranges from feature extraction with a series of neural networks to get information about the current game state to…

Multi-agent reinforcement learning in a custom game environment to train 4 agents and have them play the mobile phone game Fate Grand Order —

This post was originally published on the Shoprunner Engineering blog here feel free to check it out and at some of the other work our teams are doing. This Dress Doesn’t Exist Our ShopRunner Data Science team allows all members to have a quarterly hack week. It is important for data science teams to…

Some tips and tricks for building image datasets — Using standardized datasets is great for benchmarking new models/pipelines or for competitions. But for me at least a lot of fun of data science comes when you get to apply things to a project of your own choosing. One of the key parts of this process is building a dataset. …

At the end of 2018 Google released BERT and it is essentially a 12 layer network which was trained on all of Wikipedia. The training protocol is interesting because unlike other recent language models BERT is trained in to take into account language context from both directions rather than just…