Workshop – Deep Learning in Practice: A Hands-On Introduction
Monday, June 20, 2022 – Caesars Palace, Las Vegas
Full day: 8:30am – 4:30pm
Important note: Each workshop participant is required to bring or rent their own laptop running Windows 10. Although this workshop requires Windows 10, the skills learned and code used will be transferrable to Mac OS and other platforms. See below for more information.
Intended Audience: Anyone who wishes to learn how to create deep learning systems using PyTorch, TensorFlow, Keras, and other popular software libraries.
Knowledge Level: Basic knowledge of machine learning terminology. Minimal programming experience with a C-family language such as Python, C/C++, C# or Java is recommended but not required.
W. W. Grainger
“I really enjoyed the workshop, and I’m looking forward to applying these techniques in my work.”
Blue Cross Blue Shield of North Carolina
“I really enjoyed your topics and breakdowns.”
“The session was very informative and I was most mind-blown by the LSTM model and how well it worked.”
“It was an incredible content and hands on experience, beside all of the best practices and advices you shared with us.”
Sodimac Homecenter (Chile)
This one-day introductory workshop dives deep. You will explore deep neural classification, LSTM time series analysis, convolutional image classification, advanced data clustering, bandit algorithms, and reinforcement learning. It’s a hands-on class; you’ll learn to implement and understand both deep neural networks as well as unsupervised techniques using PyTorch, TensorFlow, Keras, and Python. Just as importantly, you’ll learn exactly what types of problems are appropriate for deep learning techniques, and what types of problems are not well suited to deep learning.
Instructor James McCaffrey leads Microsoft Research’s CEO-mandated initiative to transfer deep learning intelligence into all products, services, and supporting systems across the enterprise. Workshop participants will access much of the same state-of-the-art training material used for this work at Microsoft. Along the way, James will cover case studies detailing large-scale deployments for their internal clients that have generated astounding ROIs.
During the day, workshop attendees will gain the following practical hands-on experience:
- How to prepare, normalize, and encode data for deep learning systems.
- How to install deep learning libraries including TensorFlow, Keras, and PyTorch, and the pros and cons of each library.
- How to create deep learning predictive systems for various kinds of data: classical business data, time series data (such as sales data), image data (such as the famous MNIST dataset for handwriting recognition), and text/document data (such as legal contracts). These datasets are a great place to start – however, for the more experienced attendee, even more challenging, “next level” datasets, such as for object recognition, will be optionally available.
This workshop assumes you have a basic knowledge of machine learning terminology but does not assume you are a machine learning expert. Some theory will be presented but only enough to help you understand how to make a practical, working deep learning system. This is a code-based workshop, so some programming experience will be helpful. However, beginners will be able to follow along but may have to work a bit harder to keep up.
Hardware: Bring Your Own Laptop
Important note: Each workshop participant is required to bring their own laptop.
You are encouraged to bring a Windows 10 or 11 laptop if you have one available, but a Mac laptop will work as well. Click here for more information about this as well as pre-install instructions for both platforms.
Assistants will also be on hand to help attendees with hardware/software issues.
Attendees receive an electronic copy of the course materials and related code at the conclusion of the workshop.
- Workshop starts at 8:30am
- Morning Coffee Break at 10:30am – 11:00am
- Lunch at 12:30pm – 1:15pm
- Afternoon Coffee Break at 3:00pm – 3:30pm
- End of the Workshop: 4:30pm
James McCaffrey, Senior Scientist Engineer, Microsoft Research
James McCaffrey works for Microsoft Research in Redmond, Wash. James explores applied deep machine learning and AI. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.
Dr. Leo Betthauser, Lead Data Scientist, Microsoft
Leo Betthauser works at Microsoft Research in Redmond, Wash. Leo has a Ph.D. in mathematics from the University of Florida where he studied applied algebraic topology. Leo is currently exploring the application of deep neural techniques to cyber security. In his spare time, Leo enjoys traveling, cooking, and skiing.