A Hands-on Introduction to Deep Learning with DeepForge
2020-11-08, 17:45–19:45, Times in UTC

This tutorial will provide a hands-on introduction to deep learning using DeepForge, a gateway to deep learning for scientific computing. DeepForge provides an easy to use, yet powerful visual interface to facilitate the rapid development of deep learning models by novices as well as experts. Utilizing a cloud-based infrastructure, built-in version control and multi-user collaboration support, DeepForge aims to help with the steep learning curve of machine learning. It promotes reproducibility, data provenance, and enables remote execution of machine learning pipelines on various compute platforms. The tool currently supports TensorFlow/Keras and integrates with SciServer (among others).

The tutorial will start with a brief background on some of the basics of machine learning and deep learning then proceed into a hands-on example training a neural network to predict redshift values from galaxy spectra. The example will be end-to-end starting with the exploration of the original dataset (checking for common problems like class imbalance). The tutorial will finish with the evaluation of the trained model including visualizing the data in the learned feature space.

The tutorial will be provided using DeepForge, attendees will need a laptop with a web browser and a (free) SciServer account.


Theme – Science Platforms and Data Lakes, Machine Learning, Statistics, and Algorithms, Data Processing Pipelines and Science-Ready Data, Open Source Software and Community Development in Astronomy