It’s one thing to build a Machine Learning model, it’s another thing to effectively deploy it in your business. To navigate the challenges of moving Machine Learning models through production and deployment, it’s essential to have a strong understanding of MLOps and Data Engineering.
It’s perhaps unsurprising, then, that the MLOps and Data Engineering was a popular track at ODSC East Virtual this April. Accordingly, we’ve built a video series comprising the top MLOps and Data Engineering talks, workshops, and training sessions from the conference, the first two of which are free when you sign up for the Learn AI platform.
[Related article: What to Expect from the ODSC Europe 2020 Virtual Conference]
In the Defense of Data: Delivering Value During a Global Crisis
Alexander Dean, Co-founder and Chief Executive Officer at Snowplow Analytics, has pursued his interest in functional programming, cloud-based architectures, big data technologies, innovation, and organizational change throughout his career, which has included positions at OpenX, Deloitte Consulting, and Fathom Partners and Keplar LLP.
In this session, Alexander Dean discusses how to effectively communicate the value added by data capability and intelligence to company objectives no matter the business environment. Additionally, He will present strategies for deepening the value created.
Journey to Scalable AI: Lesson Learned with Examples
With 15 years of experience in Finance, Operations, Actuarial, and Analytics, William Drake, the Senior Director of Advanced Analytics at Nationwide, is dedicated to implementing scalable AI in the business environment.
In this session, William Drake shares his experience with implementing scalable AI to most effectively use advanced analytics to generate insights and make business decisions. He discusses the two fundamental changes–technological and cultural–that are necessary to deliver scalable AI in a company.
This video series also includes:
Talks (45 minutes each)
- Successfully Build and Scale AI Organizations Beyond the MVP – Sarah Aerni, PhD
- Raising Your Analytics from Infancy to Maturity – Dr. Brett Wujek
- Wenju: A Solution Platform for Enterprise AI – Changfeng Charles Wang, PhD
- How Retailers Can Automate AI/ML Minutes – Hiroaki Shioi
- From Graph DBs to Topological Data Analysis: Data Science Applications in Financial Services – Daniel Ferrante, PhD
- Introduction to Apache Airflow – Tomasz Urbaszek and Jarek Potiuk
- DevOps for Machine Learning and Other Half-Truths: Processes and Tools for the ML Life Cycle – Kenny Daniel
- Simplifying Data Science with Delta Lake and ML Flow – Matei Zaharia, PhD
- Scaling your ML Workloads from 0 to Millions of Users – Julien Simon
Workshops (90 minutes each)
- Streaming Decision Intelligence and Predictive Analytics with Spark 3 – Scott Haines
- Gaining Machine Learning Observability – Josh Benamram and Evgeny Shulman
- Accelerate AI/ML Workflows in Hybrid Cloud with Red Hat OpenShift Kubernetes Platform and Cognitive Scale Certifai – Trevor McKay, Sanjay Kottaram, and Luke Twardowski
- Kedro + MLflow – Reproducible and Versioned Data Pipelines at Scale – Tom Goldenberg
- AI Operationalization with Governance and Model Risk Management – Sourav Mazumder
Training Sessions (4 hours each)
- Contribute to Apache Airflow – Tomasz Urbaszek and Jarek Potiuk
- Ray: A System for High-performance, Distributed Python Applications – Dean Wampler, PhD
[Related article: What Virtual Data Science Training Will be Like at ODSC Europe 2020]
Purchase an ODSC Europe Virtual All-Access pass or Bootcamp pass to get full access to all of the training sessions, workshops, and talks included in this series. The talks above represent the breadth of content that you’ll find at ODSC Europe 2020 – register now and continue your training this September!
