Comparing Elixir and Python when working with Simple Neural Networks

Lucas Tavano (an undergraduate student at the Federal University of Technology - Paraná, where I work) and I are going to present "Comparing Elixir and Python when working with Simple Neural Networks" at Code BEAM America 2022.

Abstract

With a wide range of libraries focused on the machine learning market, such as TensorFlow, NumPy, Pandas, Keras, and others, Python has made a name for itself as one of the main programming languages. In February 2021, José Valim and Sean Moriarity published the first version of Numerical Elixir (Nx), a library for tensor operations written in Elixir. Nx aims to allow the language to be a good choice for GPU-intensive operations.

This talk aims to compare Python and Elixir when training convolutional neural networks using MNIST and CIFAR-10 datasets as examples, analyzing development experience, and performance difference.

OBJECTIVES

• Teach about the new Nx library for Elixir
• Compare Nx and Keras by the use of resources and time to train similar neural networks
• Talk about the experience of developing in both languages and how different this experience was.

AUDIENCE

• Numerical Elixir (Nx) interested people
• Python AI developers
• Data scientists

The event will take place at Mountain View, California, USA from November 1st (if you include trainings) to November 4th. We will be there in person. Access the event site here https://codebeamamerica.com/. It is also possible to attend it online.

See you there!