Sep 9–12, 2019

Tutorials

These expert-led presentations on Tuesday, September 10 give you a chance to dive deep into the subject matter. Please note: to attend tutorials, you must be registered for a Gold or Silver pass; does not include access to training courses on Monday or Tuesday.

Tuesday, September 10

Add to your personal schedule
9:00am12:30pm
Location: LL21 A/B
In this workshop, you will get hands-on experience in developing intelligent AI assistants based entirely on machine learning and using only open source tools - Rasa NLU and Rasa Core. You will learn the fundamentals of conversational AI and the best practices of developing AI assistants that scale and learn from real conversational data. Read more.
Add to your personal schedule
9:00am12:30pm
Location: LL21 C/D
Skyler Thomas (MapR)
The popular open source Kubeflow project is one of the best ways to start doing machine learning and AI on top of Kubernetes. However, Kubeflow is a huge project with dozens of large complex components. In this hands-on session, we will learn about the Kubeflow components and how they interact with Kubernetes. We explore the machine learning lifecycle from model training to model serving. Read more.
Add to your personal schedule
9:00am12:30pm
Location: 230 B
Ira Cohen (Anodot)
The goal of the tutorial is to learn and experience what it takes to be a manage machine learning (ML ) based products. In the tutorial we will go through the cycle of developing machine learning based capabilities (or entire products) and the role of the (product) manager in each step of the cycle. Read more.
Add to your personal schedule
9:00am12:30pm
Location: Almaden Ballroom
Jason Dai (Intel), Yuhao Yang (Intel), Jiao(Jennie) Wang (Intel), Guoqiong Song (Intel)
Jason Dai, Yuhao Yang, Jennie Wang, and Guoqiong Song explain how to build and productionize deep learning applications for big data with Analytics Zoo—a unified analytics and AI platform that seamlessly unites Spark, TensorFlow, Keras, and BigDL programs into an integrated pipeline—using real-world use cases from JD.com, MLSListings, the World Bank, Baosight, and Midea/KUKA. Read more.
Add to your personal schedule
9:00am5:00pm
Location: 230 C
Kristian Hammond (Northwestern Computer Science)
Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Rather than focusing on the technologies alone, Kristian Hammond provides a practical framework for understanding your role in problem solving and decision making. Read more.
Add to your personal schedule
9:00am12:30pm
Location: LL21 E/F
Lukas Biewald (Weights and Biases)
Introduction to building and deploying LSTMs, GRUs and other text classification techniques using Keras and Scikit Learn. Read more.
Add to your personal schedule
9:00am12:30pm
Location: 231
Paris Buttfield-Addison (Secret Lab), Tim Nugent (lonely.coffee), Mars Geldard (University of Tasmania)
Are you a scientist who wants to test a research problem without building costly and complicated real-world rigs? A self-driving car engineer who wants to test their AI logic in a constrained virtual world? A data scientist who needs to solve a thorny real-world problem without touching a production environment? Have you considered simulation-driven ML problem solving with a game engine? Read more.
Add to your personal schedule
1:30pm5:00pm
Location: LL21 C/D
Boris Lublinsky (Lightbend), Dean Wampler (Lightbend)
This hands-on tutorial examines production use of ML in streaming data pipelines; how to do periodic model retraining and low-latency scoring in live streams. We'll discuss Kafka as the data backplane, pros and cons of microservices vs. systems like Spark and Flink, tips for Tensorflow and SparkML, performance considerations, model metadata tracking, and other techniques. Read more.
Add to your personal schedule
1:30pm5:00pm
Location: 230 B
Chris Butler (IPsoft)
Purpose, a well-defined problem, and trust from people are important factors to any system, especially those that employ AI. Chris Butler leads you through exercises that borrow from the principles of design thinking to help you create more impactful solutions and better team alignment. Read more.
Add to your personal schedule
1:30pm5:00pm
Location: Almaden Ballroom
Mo Patel (Independent)
This tutorial will focus on all aspects of the PyTorch lifecycle via hand on examples such as image classification, text classification, and linear modeling. Other aspects of machine learning such as transfer learning, data modeling and deploying to production will be covered via immersive labs. Read more.
Add to your personal schedule
1:30pm5:00pm
Location: 231
Robert Nishihara (UC Berkeley), Philipp Moritz (UC Berkeley), Ion Stoica (UC Berkeley)
Ray is a general purpose framework for programming your cluster. We will lead a deep dive into Ray, walking you through its API and system architecture and sharing application examples, including several state-of-the-art AI algorithms. Read more.
Add to your personal schedule
1:30pm5:00pm
Location: LL21 A/B
Neil Conway (Determined AI), Yoav Zimmerman (Determined AI)
Success with deep learning requires understanding more than just TensorFlow or Keras. In this tutorial, we will describe a range of practical problems faced by DL practitioners and the software tools and techniques needed to address them, including data prep/augmentation, GPU scheduling, hyperparameter tuning, distributed training, metrics management, deployment, and mobile/edge optimization. Read more.
Add to your personal schedule
1:30pm5:00pm
Location: LL21 E/F
Joel Grus (Allen Institute for Artificial Intelligence)
This tutorial will briefly discuss what modern neural NLP looks like, after which we'll train some models, write some code, and learn how you can apply these techniques to your own datasets and problems. Read more.

Contact us

confreg@oreilly.com

For conference registration information and customer service

partners@oreilly.com

For more information on community discounts and trade opportunities with O’Reilly conferences

Become a sponsor

For information on exhibiting or sponsoring a conference

Contact list

View a complete list of O'Reilly AI contacts