We have an exciting main talk followed by a lightning talk planned for you.

Neural networks are powerful beasts that give you a lot of levers to tweak! The sheer size of customizations that they offer can be overwhelming to even seasoned practitioners. In this talk, Lavanya will give you a framework for making smart decisions about your neural network architecture!

We’ll explore lots of different facets of neural networks in this talk, including how to setup a basic neural network (including choosing the number of hidden layers, hidden neurons, batch sizes etc.) We’ll learn about the role momentum and learning rates play in influencing model performance. And finally we’ll explore the problem of vanishing gradients and how to tackle it using non-saturating activation functions, BatchNorm, better weight initialization techniques and early stopping.

We hope this guide will serve as a good starting point in your adventures!

Ligthtning talk: Upkar will introduce the Model Asset eXchange (MAX) on IBM Developer, a place where you can find and use free open source deep learning models for text, image, audio, and video processing. The exchange makes ready-to-use deep learning models available that have been well tested, are free to use and include provenance. The curated list includes deployable models that you can run as a microservice locally or in the cloud on Docker or Kubernetes, and trainable models where you can use your own data to train the models.

- machine with a functioning browser - all the training happens in the cloud anyways!

Lavanya Shukla: Lavanya is a machine learning engineer @ Weights and Biases. She began working on AI 10 years ago when she founded ACM SIGAI at Purdue University as a sophomore. In a past life, she taught herself to code at age 10, and built her first startup at 14. She's driven by a deep desire to understand the universe around us better by using machine learning. You can find her on twitter @lavanya.ai.

Upkar Lidder: Upkar is a Full Stack Developer and Data Wrangler with a decade of development experience in a variety of roles. He can be seen speaking at various conferences and participating in local tech groups and meetups.  He is currently curious about magic behind Machine Learning and Deep Learning. Upkar went to graduate school in Canada and currently resides in the United States.

Designing Your Neural Networks: A Step By Step Walkthrough