Deep Learning with PyTorch and Transfer Learning – AI Workshop II

8 HR CLASS – Deep Learning with PyTorch and Transfer Learning

TICKETS PURCHASE THROUGH EVENTBRITE:
https://www.eventbrite.com/e/deep-learning-with-pytorch-and-transfer-learning-ai-workshop-by-sfbay-acm-tickets-64856725211

Abstract
PyTorch is the fastest growing framework to build deep learning algorithms. In this full-day workshop, we will cover the foundational elements of PyTorch and provide an intuitive understanding of model development from scratch. To solve real-world problems, we will cover a very critical area of AI called Transfer Learning, where you can build models on top of those created by Google and others. So if you are looking to expand your skill set in AI with the latest tools and techniques, this is a workshop you do not want to miss.

Content: You will have access to all the notebooks, training material to build your own apps. You should be able to directly work on these using Google Colab. For the Workshop itself, we will have AWS instances available for use.

Tickets:
$150 – Early Bird Registration [until 9/6]
$175 – Regular Registration
Group rate $130 / person (Contact SF Bay Chapter of the ACM, yshroff “at” g_m_a_i_l for more information about Registration)
Location: To be announced shortly.

Key topics covered
• Fundamentals and application of ML / DL Tools, techniques with a focus on PyTorch
• .Lab – using PyTorch to build and train deep neural networks. Cover image classification
• PyTorch deep dive (Convolutional Neural networks, Recurrent Neural networks, Fault detection)
• Lab – Build and train advanced detection models (different use cases)
• Transfer learning
• Lab – Transfer learning
• Optimizing your solution for deployment
• Lab – OpenVINO, TorchScript

You can expect to take-away from the workshop
•Theoretical underpinning of Deep Learning technologies
• Practical application of DL frameworks to business problems

TARGET AUDIENCE would include people who …
• are comfortable in programming
• may already work on consulting projects or in some technical business problem solving role.
• It is helpful if you have tried Python, Spark and BigDL before.
• You are invited to submit a description of your upcoming machine learning projects or vertical. The instructor will review and may try to incorporate some ideas in the class. Through the meetup site, on the left margin, use the [contact] button.

We are seeking TA’s who know ML to help the audience. TA applicants should contact the instructor in advance. Use the [contact] button on the left, send email, phone, LinkedIn and ML experience).

BEFORE THE CLASS, PREPARATIONS & PRE-LOADING:
• For all workshops we will use Jupiter notebooks with Python, Spark and BigDL.
• For fun, play around with some neural nets at the TensorFlow Playground (http://playground.tensorflow.org).

This is a lecture and lab heavy workshop. You’re encouraged to attend our Data Science SIG earlier that week to get the fundamental concepts. We will have several TAs on-site to help with the learning process, but expect the class to move at a fairly fast clip!

SCHEDULE

8:00 – 8:30 arrive, register, coffee, network
8:30 – 10:00 lecture / lab
15 min break, coffee
10:15 – 11:30 lecture / lab
45 min break for lunch
12:15 -1:45 lecture / lab
15 min break, coffee, small snacks
2:00 – 3:30 lecture / lab
15 min break, coffee, small snacks
3:45 – 5:15 lecture / lab
15 min Q&A

Instructors:
Ravi Ilango (Data Scientist, FogHorn)

Greg Makowski (https://www.linkedin.com/in/gregmakowski/) has been deploying data mining models for 25 years as the “neural net guy” at American Express/Epsilon. He has developed the analytic internals and automation for 6+ enterprise software systems or SaaS systems. His first convolutional neural net was trained in 1991, a Time Delay Neural Net for speech recognition. Vertical experience includes financial services (credit card, retail banking, bond pricing, ACH payments, fraud detection, customer relationship management (mail, phone, email, banner), retail supply chain among others. He always has something to learn from everybody.