Summary of key application-agnostic talks from Spark+AI Summit 2020, focusing on scaling and optimizing deep learning models.
A step-by-step tutorial on deploying a custom PyTorch machine learning model to production using AWS Lambda and the Serverless Framework.
A comparative analysis of the underlying architecture and design principles of TensorFlow and PyTorch machine learning frameworks.
Explores improving recommender systems using graph-based methods and NLP techniques like word2vec and DeepWalk in PyTorch.
A guide to building a recommender system using PyTorch on a laptop, covering data acquisition, parsing, and multiple modeling techniques.
A satirical look at AI development and government funding, imagining a fictional 'Ministry of Silly Models' in the UK.
An annotated, line-by-line implementation of the Transformer architecture from 'Attention is All You Need' in PyTorch.
A comparison of PyTorch and TensorFlow deep learning frameworks, focusing on programmability, flexibility, and ease of use for different project scales.
