Applied AI : Workshop & Tutorial Sessions

– Hands-on workshops and in-depth tutorials –

Important Workshop Prerequisite 

To facilitate the hands-on sessions, we are delighted to announce that DataRobot, our diamond partner, is providing hands-on session attendees with free access to their AI platform. 

Many of our workshops  and tutorials will utilize the AI Platform for instruction and collaboration. It automates the end-to-end process for building, deploying, and maintaining AI at scale and also provides feature engineering, auto model evaluation, and advanced machine learning techniques. It comes preloaded with models and datasets so you can get started prior to the event. Please note: YOU MUST BE REGISTERED TO GET FREE ACCESS to the AI Platform

Applied AI Schedule – All times are Eastern Standard Time
Business Analytics Track
Data Science Track
MLOps & DevOps Track
Software Engineering Track
Business Analytics Track
Data Science Track
MLOps & DevOps Track
Software Engineering Track
10:00
Speaker Panel: Applied AI – Stories From the Front Lines
Speaker Panel: Applied AI – Stories From the Front Lines image
Ben Taylor, PhD
Chief AI Evangelist | DataRobot
Speaker Panel: Applied AI – Stories From the Front Lines image
Sarah Nooravi
Sr. Financial Analyst | Snap Inc
Speaker Panel: Applied AI – Stories From the Front Lines image
Angela Baltes
Institutional Data Scientist | UNM
Speaker Panel: Applied AI – Stories From the Front Lines image
Jen Underwood
Director Product Strategy | Oracle
Speaker Panel: Applied AI – Stories From the Front Lines image
David Langer
VP of Analytics | Schedulicity
Speaker Panel: Applied AI – Stories From the Front Lines image
Favio Vázquez
CEO | Closter
10:00
Speaker Panel: Applied AI – Stories From the Front Lines
Speaker Panel: Applied AI – Stories From the Front Lines image
Ben Taylor, PhD
Chief AI Evangelist | DataRobot
Speaker Panel: Applied AI – Stories From the Front Lines image
Sarah Nooravi
Sr. Financial Analyst | Snap Inc
Speaker Panel: Applied AI – Stories From the Front Lines image
Angela Baltes
Institutional Data Scientist | UNM
Speaker Panel: Applied AI – Stories From the Front Lines image
Jen Underwood
Director Product Strategy | Oracle
Speaker Panel: Applied AI – Stories From the Front Lines image
David Langer
VP of Analytics | Schedulicity
Speaker Panel: Applied AI – Stories From the Front Lines image
Favio Vázquez
CEO | Closter
10:00
Speaker Panel: Applied AI – Stories From the Front Lines
Speaker Panel: Applied AI – Stories From the Front Lines image
Ben Taylor, PhD
Chief AI Evangelist | DataRobot
Speaker Panel: Applied AI – Stories From the Front Lines image
Sarah Nooravi
Sr. Financial Analyst | Snap Inc
Speaker Panel: Applied AI – Stories From the Front Lines image
Angela Baltes
Institutional Data Scientist | UNM
Speaker Panel: Applied AI – Stories From the Front Lines image
Jen Underwood
Director Product Strategy | Oracle
Speaker Panel: Applied AI – Stories From the Front Lines image
David Langer
VP of Analytics | Schedulicity
Speaker Panel: Applied AI – Stories From the Front Lines image
Favio Vázquez
CEO | Closter
10:00
Speaker Panel: Applied AI – Stories From the Front Lines
Speaker Panel: Applied AI – Stories From the Front Lines image
Ben Taylor, PhD
Chief AI Evangelist | DataRobot
Speaker Panel: Applied AI – Stories From the Front Lines image
Sarah Nooravi
Sr. Financial Analyst | Snap Inc
Speaker Panel: Applied AI – Stories From the Front Lines image
Angela Baltes
Institutional Data Scientist | UNM
Speaker Panel: Applied AI – Stories From the Front Lines image
Jen Underwood
Director Product Strategy | Oracle
Speaker Panel: Applied AI – Stories From the Front Lines image
David Langer
VP of Analytics | Schedulicity
Speaker Panel: Applied AI – Stories From the Front Lines image
Favio Vázquez
CEO | Closter
10:45
Deep Learning in 10 Minutes or Less with AutoML

Workshop, 90 Minutes, Watch now!

 

AutoML is coming to deep learning. Traditional deep learning models would take data scientists weeks to code and tune. Learn how to take multimodal datasets, mixing of tabular and unstructured data (images, audio, video), and create accurate deep learning models in under 10 minutes with DataRobot. AutoML lets users have access to the latest frameworks like Keras, but with a push of a button be able to access transparent interpretability tools like feature impact, partial dependence, and prediction explanations. In this session, we will reveal some recent breakthroughs in deep learning and walk through some detailed examples from data to deployment…more details

Deep Learning in 10 Minutes or Less with AutoML image
Emily Webber, PhD
Data Scientist | DataRobot
Deep Learning in 10 Minutes or Less with AutoML image
Ben Taylor, PhD
Chief AI Evangelist | DataRobot
10:45
AI Crash Course – Adding ML to Your Software Projects in an Hour

Workshop, 90 Minutes,  Watch now!

In this introductory session, we will be covering the basics of making AI-powered applications, from designing a dataset to making predictions in-app. This session will be primarily focused on using REST APIs to build, deploy, and consume AI output. All samples and source code will be available on GitHub so you can follow along or experiment afterward. You will be encouraged to ask questions during and before the event!…more details

AI Crash Course – Adding ML to Your Software Projects in an Hour image
Zan Markan
Developer Advocate | DataRobot
AI Crash Course – Adding ML to Your Software Projects in an Hour image
Peter Klipfel
Backend Engineer | DataRobot
10:45
The Art of Storytelling for AI and Machine Learning

Talk, 45 Minutes, Watch now!

 

In today’s era of artificial intelligence (AI) and machine-assisted analytics, business analysts are crucial for bridging the growing data literacy gap. Successful analytical communicators don’t wait until the end of their analysis to communicate insights. Accurately defining projects, understanding what to data to use, preventing bias, and interpreting and effectively communicating findings are all important skills for helping stakeholders understand results and get the most actionable value from automated machine learning projects.In this session, Jen Underwood will walk through the best way to communicate the value of automated machine learning results with visualizations throughout the entire analytical process, from use case definition to insight implementation.You’ll learn:How to define a business use case for machine learning and AI storytellingThe process of planning, designing, and visualizing AI storiesHow to effectively translate quantitative insights and tell a compelling story throughout the complete analytical project lifecycle…more details

The Art of Storytelling for AI and Machine Learning image
Jen Underwood
Director Product Strategy | Oracle
10:45
Introduction to MLOps: The Concepts and Strategies that Get Models Reliably into Production

Workshop, 90 minutes, Watch now!

 

During this session we will be learning how to architect, instrument, deploy, and manage AI models of various types in production environments. Example code will be provided. It is recommended that attendees have a background in or familiarity with DevOps concepts…more details

Introduction to MLOps: The Concepts and Strategies that Get Models Reliably into Production image
Seph Mard
Head of Model Validation | DataRobot
11:30
Everything You Need to Know About Protecting AI Algorithms with IP

Talk, 45 Minutes, Watch now!

 

When considering Intellectual property rights typically you think of patents, trademarks and the like. But what about the IP architected into your algorithms and AI decision pipelines?  Beau Walker, a Data Scientist with a degree in Intellectual Property Law, has explored this concept his entire career. Together with Ben Taylor, PHD, they will summarize the basics and deep dive into the key factors you need to know to protect the IP inherent in your AI…more details

Everything You Need to Know About Protecting AI Algorithms with IP image
Beau Walker
Founder; Chief Data Scientist | Method Data Science
Everything You Need to Know About Protecting AI Algorithms with IP image
Ben Taylor, PhD
Chief AI Evangelist | DataRobot
12:15
Explore UK Crime Data with Pandas and Geopandas

Workshop, 90 Minutes, Watch now!

In this workshop you will learn how to expand your Python data analysis skills to geospatial data.The workshop is aimed at software engineers, data scientists, and others who are interested in data science and data analysis.

During the workshop we will analyse UK Crime Data with Pandas and GeoPandas in a Jupyter notebook. We first will look at the properties of geospatial data and explore the different commands. After you have learned the basics we will go through some exercises analysing the UK Crime Data to explore patterns and trends and create a few maps of crime rates in London… more details

Explore UK Crime Data with Pandas and Geopandas image
Yamini Rao
Developer Advocate/Community Manager | IBM
12:15
Turn your AI Models into Gold with these 5 Principles

Talk, 45 Minutes, Watch now!

Much of the success of your models will depend on customer adoption. Setting the right expectations, communicating the results, introducing the idea of risk, and integrating your models in your customers day-to-day lives are just the tip of the iceberg. In this presentation, we will be discussing 5 practical and effective principles you can use to make your models as impactful and meaningful to your customers as possible. With these principles, your customers will keep coming for more!  more details

Turn your AI Models into Gold with these 5 Principles image
Keenan Moukarzel
Data Analytics Business Lead | Freddie Mac
12:15
Building Ethics and Diversity in AI

Talk, 45 Minutes, Watch now!

 

Bias in machine learning is a significant concern as technology gets increasingly ubiquitous across many industries. Some types of bias can be attributed to limits in design and tooling; however, the bias in the training data itself is a general phenomenon. Skewed training data propagates into discriminatory AI models that amplify human prejudices.

 

Building a data labeling framework that uses a diverse set of crowd workers to collect and label the data can help reduce bias. Additionally, when you tap into a global crowd workforce you need to optimize the quality and speed of the labeling tasks, while at the same time follow ethical pricing practices so the crowd workforce is paid fair wages. This is a tough nut to crack.

 

In this talk, we present some of the frameworks and approaches to minimize bias and maintain a thriving community of highly engaged crowd workers. We will talk about:

  • A bias minimizer framework that routes data labeling tasks to the right crowd worker and maintains a healthy worker distribution for a given task.
  • An approach to ensure a fair wage for the crowd with location, skillsets, and task complexity considerations.
  • Ways to increase crowd performance and engagement with smart targeting of labeling tasks to the crowd workers who are best suited for the job.
Building Ethics and Diversity in AI image
Meeta Dash
VP Product | Appen
Building Ethics and Diversity in AI image
Monchu Chen
Principal Data Scientist | Appen
12:15
Kubernetes: Simplifying Machine Learning Workflows

Talk, 45 Minutes, Watch now!

 

You know Kubernetes is a great platform for the applications you’re running today. Most of the applications you’ll be excited about tomorrow are intelligent applications, which collect data and rely on machine learning to support essential functionality. These capabilities often seem like magic to users, but building applications and services that leverage artificial intelligence is more accessible than you might think. This workshop will show how Kubernetes, the most popular open source container orchestration platform, can increase collaboration and decrease time to value for machine learning workflows. Attendees will be able to create workflows with ease, deploy models as micro-services and monitor performance to understand when retraining is needed. We’ll focus on the open source infrastructure, tools and processes that will help you to get meaningful results from application intelligence and show why Kubernetes is the best place for data science workloads. You’ll leave having solved a real business problem interactively with powerful machine learning techniques and Kubernetes…more details

Kubernetes: Simplifying Machine Learning Workflows image
Michael Clifford
Data Scientist, AI CoE | Red Hat
Kubernetes: Simplifying Machine Learning Workflows image
William Benton
Senior Principal Software Engineer | RedHat
Kubernetes: Simplifying Machine Learning Workflows image
Sophie Watson
Senior Data Scientist | Red Hat
13:00
Getting up to Speed with Dask

Talk, 45 Minutes, Watch now!

 

Dask is a parallel computing library for Python people. This talk will be a gentle introduction to Dask, showing how you can improve the speed of data science code on your laptop with a simple “pip install”. Then we will use the same code to process big data on a cluster of machines. We will be going through an end-to-end data science pipeline, from ETL and exploratory analysis to machine learning model training and scoring… more details

Getting up to Speed with Dask image
Aaron Richter, PhD
Senior Data Scientist | Saturn Cloud
13:00
Integrating Prior Knowledge with Learning in Natural Language Processing

Talk, 45 Minutes, Watch now!

 

Prior knowledge is believed to be informative to assist the understanding of natural language and the integration of prior knowledge with machine learning models has been found useful in various NLP tasks. The prior knowledge can be categorised into two categories. Structured knowledge explicitly defined by knowledge graph and more, while unstructured knowledge implicitly contained in large text corpus. Our research focuses on the effectiveness of integrating these two kinds of prior knowledge with machine learning models on text classification and summarisation…more details

Integrating Prior Knowledge with Learning in Natural Language Processing image
Jingqing Zhang, PhD
Technical Co-founder and Head of AI | PangaeaData.AI
13:00
Just You and AI: How a Business Leader Learned AI

Talk, 45 Minutes, Watch now!

 

Do you have the desire to understand and use AI, but are unsure where to start? Edward Young was in the same position just a few years ago. He created his own path to learn AI and had some fits and starts along the way, but today he can spot use cases, help work through complex data issues, and move with ease between the data science and business teams within his organization. Ed’s story will inspire and empower you to get started and upskill yourself into a critical position within your current organization or the next.
The recommended abstract must be at least 250 words. However, ensure your abstract is succinct and speaks to both the topic and context of your presentation. This abstract will be used on an online speaker page, mobile app, and other online marketing platforms. The description must also explain what the attendee will learn from your presentation and what industry verticals are being targeted…more details

Just You and AI: How a Business Leader Learned AI image
Edward M. Young
Director of Advanced Analytic | FCA Fiat Chrysler
13:45
The Practitioner’s Data Prep Workshop

Workshop, 90 Minutes, Watch now!

Business analysts and data scientists alike spend as much as 80 percent of their time finding, cleaning, and reorganizing data. In this session, we will lead you through a tested workflow on how to prepare data for machine learning. You will leave with a handy practitioner’s guide that outlines a repeatable process to help you going forward. Then, using DataRobot Paxata, the industry leading data preparation tool, we will demonstrate point-and-click ML-assisted data prepping functionality that can help you significantly reduce the amount of time you spend getting your data ready for models…more details

The Practitioner’s Data Prep Workshop image
Shyam Ayyar
Product Manager | DataRobot
The Practitioner’s Data Prep Workshop image
Sean Smith
Director of AI Success | DataRobot
13:45
Advanced MLOps: Instrumenting CI/CD Workflows in DataRobot MLOps

Workshop, 90 Minutes, Watch now!

 

During this session we will be learning how to architect, instrument, deploy, and manage AI models of various types in production environments. Example code will be provided. It is recommended that attendees have a background in or familiarity with DevOps concepts.