Wednesday, May 17, 7:30-9:30AM

Title:

A Practical Introduction to Applied Machine Learning For Scientists

Abstract:

We've seen the rapid adoption of machine learning in many application areas recently. These include computer vision, speech recognition, biometrics, natural language processing, fin-tech, e-commerce, agri-tech, manufacturing, automotive, health-tech, biopharma, and, yes, in aerospace and space exploration. Machine learning is the underpinning of numerous advances in so called “artificial intelligence” and may rival electricity or the transistor as one of the most transformative technology catalysts the world has experienced in the last 200 years. All the hype notwithstanding, a good question technicians and scientists should ask themselves - Is machine learning a useful tool to further advance their work or research?

In this workshop, we will cut through the hype and give participants hands-on experience in several key machine learning areas including:

• Preparing data for machine learning using exploratory data analysis
• Training a model for time-series based forecasting
• Evaluating the model for accuracy
• Optimizing the model for speed and size
• Deploying the model to custom accelerator hardware
• Monitoring the model in production

We will use open-source tools such as Python and PyTorch and state-of-the-art machine learning techniques including deep learning and sequence modeling. Participants need only bring a laptop with an internet browser. The workshop will provide all the tools and the dataset. By the end of the 2-hour workshop, participants will have gained practical experience with the 360 degree lifecycle of machine learning- from data preparation, to model training, optimization, deployment, and performance monitoring. Workshop materials will be made available before the workshop for participants who want to get a head-start.

Biography:

George Williams is the Head of AI at Smile Identity, an identity management and computer vision-based biometrics provider. He has held senior leadership roles in software engineering, system design, data science, and AI research, including tenures at Apple's New Product Architecture group and at New York University's Courant Institute. He can talk on a broad range of topics at the intersection of e-commerce, machine learning, cybersecurity, computer hardware, and computer science. He is an author of several research papers in computer vision and deep learning, published at NeurIPS, CVPR, ICASSP, ICCV, and SIGGRAPH. George is regularly invited to present at meetups and technology conferences, including recent talks at Blackhat, Open Data Science Conference, Apache Spark Summit, JupyterCon, AnacondaCon, and Space Computing. He is a track chair at the Valleyml.ai conference and as a chair for the Neural Information Processing Conference.

More speakers to be announced...