Accelerate Your Knowledge and Career
AI is transforming industry and presenting unparalleled challenges and opportunities. Hear expert speakers explain essential AI topics such as machine learning, deep learning, predictive analytics, and many more. Learn the essential skills of tomorrow, today.
Deploying your AI/FML investments
Applications of Deep Learning in Aerospace and Building Systems
This talk demonstrates using DBN, DAE, DRL and GAN in five different aerospace and building systems applications.
Applied Finance - The Third Culture
In this session we explore why it is important that we bridge the gap between the traditional data science cultures and applied finance.
Machine Learning for Mobile Sensing Applications
In this talk we’ll detail the kinds of sensor data available from mobile phones and other smart devices.
Deep Learning Techniques for Vision
This is an extremely hands-on course to take students from little knowledge of deep learning to comfort building vision models with Keras and TensorFlow.
Pavlov’s Sandman: Issues detecting snorers, training oneself not to snore via shock collar, war crime technicalities, and how to avoid all three
This talk is the journal of the explorations of a total novice audio analyst, seeking to correctly identify snores, and shock himself appropriately.
TRANSFER LEARNING: APPLICATIONS FOR NATURAL LANGUAGE UNDERSTANDING
This talk focuses on language related use cases for customer service, search, question answer, self-help and consumer finance. We'll also have some fun with applications of transfer learning.
Standardized Data Science: The Team Data Science Data Process - with a practical, example in Python
Crawling the internet Data Science Within a Large Engineering System
We will discuss some of the special considerations impacting a data scientist when designing solutions to improve decision-making deep within software infrastructure.
How to use Satellite Imagery to be a Machine Learning Mantis Shrimp
In this session we are going to start by showing you how satellite imagery actually allows you to “see” in more bands of color than the mantis (how about 26 bands) – each band is a massive amount of data about the earth.
THE PAST, PRESENT, AND FUTURE OF AUTOMATED MACHINE LEARNING
In this talk, Randy will draw from his AutoML research experience to discuss the benefits of AutoML and highlight some promising future directions of the field.
Introduction to Quant Finance with Quantiacs Toolbox
THE ADOPTION OF AI IN BUSINESS: OPPORTUNITIES AND CHALLENGES
MIT Sloan Management Review’s recent research on AI and business strategy offers a "state of the state" of AI adoption inside corporations. This session will provide an overview of organizational readiness for and adoption of AI across sectors.
PROJECT FEELS: DEEP TEXT MODELS FOR PREDICTING THE EMOTIONAL RESONANCE OF NEW YORK TIMES ARTICLES
Topics discussed will be active learning, deep learning, Bayesian inference and causality.
Bringing Your Deep Learning Algorithms to Life: From Experiments to Production Use
We will learn how to take Machine Learning and Deep Learning programs into a production use case and manage the full production lifecycle.
FROM NUMBERS TO NARRATIVE: DATA STORYTELLING
Session will cover: The essential elements of a good data story, Chart design and why it matters, Common chart design errors, and The Gestalt principals of visual perception and how they can be used to tell better stories with data.
Building an Image Search Service from Scratch
We are bringing a workshop on how you would go about building your representations, both for image and text data.
DATAOPS: ENTERPRISE DATA THAT DOESN’T SUCK
During his talk, Andy will highlights the converging factors that allow non-data native companies transform their data engineering organizations to catch up with data-native companies like Facebook, Google and Amazon.
Getting to Grips with the Tidyverse (R)
In this tutorial, we'll cover some of the core features of the tidyverse, such as dplyr (the workhorse of the tidyverse), string manipulation, linking directly to databases and the concept of tidy data.
DEEP LEARNING FOR DEVELOPERS
This covers concepts of Neural Networks and Deep Learning in simple terms, with minimal theory and math. Then, through code-level demos based on Apache MXNet, we're building, training and using models based on different types of networks.
MULTIVARIATE TIME SERIES FORECASTING USING STATISTICAL AND MACHINE LEARNING MODELS
This lecture discusses the formulation Vector Autoregressive (VAR) Models, one of the most important class of multivariate time series statistical models, and neural network-based techniques.
GRADIENT DESCENT, DEMYSTIFIED
Viewers will leave the talk with a better understanding of iterative optimization and a template of their own for implementing GD in Python, should they feel this would enrich their understanding.
RACIAL BIAS IN FACIAL RECOGNITION SOFTWARE
This talk will cover the basics of facial recognition and the importance of having diverse datasets when building out a model. We’ll explore racial bias in datasets using real world examples and cover a use case for developing an OpenFace model.
DATAFY ALL THE THINGS
This session empower you to curate & create your own data sets. You’ll learn how to parse unstructured text, harvest data from interesting websites and public APIs and about capturing and dealing with sensor data.
Experience ODSC Live!
Hear from the best and brightest in data science and AI at ODSC East
Tour Livestream brings you of the best of the best. Based on pre-registration popularity we bring you both the top speakers and the most highly anticipated sessions to ensure you get the best of ODSC East 2019
A Few of our Distinguished Keynotes and Invited Speakers
Founder and CEO at Matroid, a computer vision startup, and an Adjunct Professor at Stanford University. His work focuses on Machine Learning, Distributed Computing, and Discrete Applied Mathematics. His awards include a KDD Best Paper Award and the Gene Golub Outstanding Thesis Award. He has been working on Artificial Intelligence since 2005 when, at the age of 18, he was part of Google’s AI research team.
Accelerate AI'18 Keynote
Technical Director of Applied AI at Google, where he leads AI experiments and collaborates with Google Product and Engineering for AI products. He engages deeply with Global F500 enterprises to unlock strategic value with AI. Previously, Ron was the founding CEO of Think Big Analytics. Ron holds a BS in math and computer science with honors from McGill University and a master’s degree in computer science from MIT, where he also pursued a PhD.
Accelerate AI'18 Keynote
Virginia Eubanks, PhD
is an associate professor at SUNY and author of Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. As models become prolific in our society practitioners must be of vigilant to the unintentional consequences that Virginia exposes.
ODSC West'18 Keynote
Dr Kirk Borne
Kirk Borne is a data scientist and an astrophysicist who has used his talents at Booz Allen since 2015. He was professor of astrophysics and computational science at George Mason University (GMU) for 12 years. Kirk spent nearly 20 years supporting NASA projects.
ODSC East'18 Invited Speaker