AI Learning Accelerator
Ram Ravichandran

Building an effective AI practice

Jan Freyberg

Interactive data visualization in Python

We will go through python libraries that make this extra development as frictionless as possible, and produce interactive visualizations with as little code as possible.

Anyi Wang

Recommending the best hotels at TripAdvisor

Kirk Borne

Solving the Data Scientist's Dilemma - The Cold Start Problem

How can you maximize the data science outcomes, benefits, and applications when faced with the cold start problem?

Tomasz Adamusiak

Knowledge Graphs in Financial Technology – Future or Hype

Sourav Dey

Applications of Mixed Effects Random Forests

ODSC West'18

Analyzing Space - Spatial Data Science Methods

Alexander Statnikov

Machine Learning Powers Better Decisions in Financial Services

Ben Vigoda

A Breakthrough for Natural Language

Michael Mahoney, PhD

Matrix Algorithms at Scale: Randomization and using Alchemist to bridge the Spark-MPI gap

We describe use cases from scientific data analysis that motivated the development of Alchemist and that benefit from this system.

Alex Pentland

Blockchain and AI, or future data systems must be built differently

Alejandro Jaimes, PhD

Challenges and Opportunities in Applying Machine Learning

Skipper Seabold

Introduction to Python for Data Science

We'll take a closer look at how Python can be leveraged to build effective data science workflows.

Alex Sandy Pentland

Blockchain AI, or Future Data Systems Must Be Built Differently

Joshua Cook

Engineering For Data Science

This talk will discuss Docker as a tool for the data scientist.

Andreas Mueller, PhD

Introduction to Machine Learning

This talk gives a general introduction to machine learning, as well as introduces practical tools for you to apply machine learning in your research.

Aedin Culhane, PhD

Enter the Matrix: Unsupervised feature learning with matrix decomposition to discover hidden knowledge in high dimensional data

Tyler Freckmann

Deep Learning in Real-Time

We will take a tour of different DL algorithms and applications, learn how different DL models are built, and see how to deploy DL models for real-time processing with SAS technology.

Jason Prentice

Mapping the Global Supply Chain Graph

Jon Peck

Deploying your AI/FML investments

Amit Surana, PhD

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.

Stephen Lawrence

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.

Michael Bell, PhD

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.

Lukas Biewald

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.