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As data science extends its reach across an enterprise, the need for better management, workflow, production and deployment practices increases. The challenges of deploying and monitoring models in production, managing data science workflows and teams, and understanding ROI are a few of the issues organizations wrestle with.
Learn best practices for effective data science management
Sessions in this broad focus area will look at uses cases, best practices, and stories from the field to show how to effectively incorporate data science practice into the wider business process. This focus area will look beyond data sourcing and modeling towards the many challenges teams need to overcome to effectively apply data science in their organization.
Some of Our Past MLOps Speakers
Yaron Haviv
Yaron Haviv is a serial entrepreneur who has been applying his deep technological experience in AI, cloud, data and networking to leading startups and enterprises since the late 1990s. As the Co-Founder and CTO of Iguazio, Yaron drives the strategy for the company’s MLOps platform and led the shift towards the production-first approach to data science and catering to real-time AI use cases. He also initiated and built Nuclio, a leading open source serverless framework with over 4,000 Github stars and MLRun, a cutting-edge open source MLOps orchestration framework.
Prior to co-founding Iguazio in 2014, Yaron was the Vice President of Datacenter Solutions at Mellanox (now NVIDIA – NASDAQ: NVDA), where he led technology innovation, software development and solution integrations. He also served as the CTO and Vice President of R&D at Voltaire, a high-performance computing, IO and networking company which floated on the NYSE in 2007 and was later acquired by Mellanox (NASDAQ:MLNX).
Yaron is an active contributor to the CNCF Working Group and was one of the foundation’s first members. He sits on the Data Science Committee of the AI Infrastructure Alliance (AIIA), of which Iguazio is a founding member. He is co-authoring a book on Implementing MLOps in the Enterprise for O’Reilly. Yaron presents at major industry events worldwide and writes tech content for leading publications including TheNewStack, Hackernoon, DZone,Towards Data Science and more.
Implementing Gen AI in Practice(Track Keynote)
Joe Dery, PhD
Joe Dery joined Western Governors University’s College of IT as the VP & Dean of Data Analytics in summer, 2022. At WGU, Joe is working to help more than 3,000 current analytics students learn how to effect change in their professional roles – surgically balancing a combination of mathematics, data management, programming, and business influence skills. Prior to joining academia full-time, Joe spent much of his corporate career working for EMC – and later, Dell Technologies – where he joined as a “hands-on-keyboard” Data Scientist in 2011. Joe went on to hold leadership positions in Dell’s Sales, Finance, and Supply Chain organizations driving efforts in Data Science, Business Intelligence, Digital Strategy, and Digital Transformation. Across these domains, Joe’s efforts touched a wide variety of business problems, including ML-driven sales quota allocations, sales forecasting & opportunity prioritization, customer cross-sell/whitespace targeting, addressable marketing opportunity sizing, sales territory optimization, supply chain planning optimization, data/analytics literacy training, and self-service BI. Building from his experiences, Joe is often invited to speak on the crucial role of decision intelligence frameworks, change management, and “improv” in bringing analytics solutions to life. Joe holds a Ph.D in Business Analytics & an M.S. in Marketing Analytics, both from Bentley University.
Unlock the Power of Data Science for Real Change: A Blueprint for Decision Intelligence(Track Keynote)
Emily Curtin
Emily is a Staff MLOps Engineer at Intuit Mailchimp, meaning she gets paid to say “it depends” and “well actually.” Professionally she leads a crazy good team focused on helping Data Scientists do higher quality work faster and more intuitively. Non-professionally she paints huge landscapes and hurricanes in oils, crushes sweet V1s (as long as they’re not too crimpy), rides her bike, reads a lot, and bothers her cats. She lives in Atlanta, GA, which is inarguably the best city in the world, with her husband Ryan who’s a pretty darn cool guy.
Containers + GPUs In Depth(Talk)
Extinguishing the Garbage Fire of ML Testing(Lightning Talks)
Florian Jacta
Florian Jacta is a specialist of Taipy, a low-code open-source Python package enabling any Python developers to easily develop a production-ready AI application. Package pre-sales and after-sales functions. He is data Scientist for Groupe Les Mousquetaires (Intermarche) and ATOS. He developed several Predictive Models as part of strategic AI projects. Also, Florian got his master’s degree in Applied Mathematics from INSA, Major in Data Science and Mathematical Optimization.
How to Build Stunning Data Science Web applications in Python – Taipy Tutorial(Workshop)
Bringing AI to Retail and Fast Food with Taipy’s Applications(Track Keynote)
Demo Session Title: Turning your Data/AI algorithms into full web apps in no time with Taipy
Abstract:
In the Python open-source ecosystem, many packages are available that cater to:
– the building of great algorithms
– the visualization of data
Despite this, over 85% of Data Science Pilots remain pilots and do not make it to the production
stage.
With Taipy, a new open-source Python framework, Data Scientists/Python Developers are able to
build great pilots as well as stunning production-ready applications for end-users.
Taipy provides two independent modules: Taipy GUI and Taipy Core.
In this talk, we will demonstrate how:
1. Taipy-GUI goes way beyond the capabilities of the standard graphical stack: Gradio,
Streamlit, Dash, etc.
2. Taipy Core fills a void in the standard Python back-end stack.
Andrew Lamb
Andrew Lamb is the chair of the Apache Arrow Program Management Committee (PMC) and a Staff Software Engineer at InfluxData. He works on InfluxDB IOx, a time series database engine written in Rust, that heavily uses the Apache Arrow ecosystem. He actively contributes to many open source software projects including the Apache Arrow Rust implementation and the Apache Arrow DataFusion query engine.
Tutorial: Introduction to Apache Arrow and Apache Parquet, using Python and Pyarrow(Workshop)
Fabiana Clemente
Fabiana Clemente is the co-founder and CDO of YData, combining Data Understanding, Causality, and Privacy as her main fields of work and research, with the mission to make data actionable for organizations. Passionate for data, Fabiana has vast experience leading data science teams in startups and multinational companies. Host of “When Machine Learning meets privacy” podcast and a guest speaker at Datacast and Privacy Please, the previous WebSummit speaker, was recently awarded “Founder of the Year” by the South Europe Startup Awards.
Missing Data: A Synthetic Data Approach for Missing Data Imputation(Workshop)
Albert Vu
Albert has skills in machine learning and big data to solve (financial) optimization problems. He developed projects of different skill levels for Taipy’s tutorial videos. He got his degree from McGill University – Bachelor of Science. Major in Computer Science & Statistics. Minor in Finance.
How to build stunning Data Science Web applications in Python – Taipy Tutorial(Workshop)
Bringing AI to Retail and Fast Food with Taipy’s Applications(Track Keynote)
Demo Talk Session Title: Turning your Data/AI Algorithms into full web apps in no time with Taipy
Abstract:
In the Python open-source ecosystem, many packages are available that cater to:
– the building of great algorithms
– the visualization of data
Despite this, over 85% of Data Science Pilots remain pilots and do not make it to the production stage.
With Taipy, a new open-source Python framework, Data Scientists/Python Developers are able to build great pilots as well as stunning production-ready applications for end-users.
Taipy provides two independent modules: Taipy GUI and Taipy Core.
In this talk, we will demonstrate how:
Taipy-GUI goes way beyond the capabilities of the standard graphical stack: Gradio, Streamlit, Dash, etc.
Taipy Core fills a void in the standard Python back-end stack.
Yuval Fernbach
Yuval Fernbach is the Co-founder & CTO of Qwak, where he is focused on building next-generation ML Infrastructure for ML teams of various sizes. Before Qwak, Yuval was an ML Specialist at AWS , where he helped AWS Customers across EMEA with their ML challenges. Previous to that, he was the CTO of the IT department of the IDF (“Mamram”).
Dean Pleban
Dean has a background combining physics and computer science. He’s worked on quantum optics and communication, computer vision, software development, and design. He’s currently CEO at DagsHub, where he builds products that enable data scientists to work together and get their models to production, using popular open-source tools.
He’s also the host of the MLOps Podcast, where he speaks with industry experts about ML in production.
Anna Jung
Anna Jung is a Senior ML Open Source Engineer at VMware, leading the open source team as part of the VMware AI Labs. She currently contributes to various upstream ML-related open source projects focusing on the project’s overall health, adoption, and innovation. She believes in the importance of giving back to the community and is passionate about increasing diversity in open source. When away from the keyboard, Anna is often at film festivals supporting independent filmmakers.
RJ He
RJ He is Zoox’s Director of Perception, where he is responsible for Zoox robotaxi’s ability to see and understand the world around them. He also leads the Zoox Boston office to assemble a world-class team of AI engineers. RJ was previously co-founder & CEO of Strio AI, an agriculture robotics startup, as well as VP Eng at Optimus Ride, an AV startup. RJ has also commanded a mechanized infantry unit, and holds an MIT PhD in autonomous systems.
Leveraging MLOps to Accelerate Autonomous Vehicle Development(Lightning Talks)
More talks, hands-on workshop and training sessions
see all sessionsWho Should Attend
Data Science is cross industry and cross enterprise, impacting many different departments across job roles and functions. This track is not only for data scientists of all levels but for anyone interested in the practice and management of data science, including:
Data scientists moving beyond model experimentation looking to understand production workflow
Data scientists seeking to improve the overall practice of management and development
Anyone interested in understanding better collaborative and agile management techniques as applied to data science
Business professionals and industry experts looking to understand data science in practice
Software engineers and technologists who need to work with data science workflows and understand the unique requirements of these systems
CTO, CDS, and other managerial roles that require a bigger picture view of data science
Technologists in the field of DevOps, databases, project management and others looking to break into data science
Students and academics looking for more practical applied training in data science tools and techniques
Why Attend?
Accelerate and broaden your knowledge of key areas in data science, including deep learning, machine learning, and predictive analytics
With numerous introductory level workshops, you get hands-on experience to quickly build your skills
Post-conference, get access to recorded talks online and learn from over 100+ high quality recording sessions that let you review content at your own pace
Take time out of your busy schedule to accelerate your knowledge of the latest advances in data science practice and management
Learn directly from world-class instructors who are the authors and contributors to many of the tools and languages used in data science today
Meet hiring companies, ranging from hot startups to Fortune 500, looking to hire professionals with data science skills at all levels
Network at our numerous lunches and events to meet with data scientists, enthusiasts, and business professionals
Get access to other focus area content, including machine learning & deep learning, data visualization, and much more
What You’ll Learn
Data science has many focus areas. The goal of this track is to accelerate your knowledge of data science through a series of introductory level training sessions, talks, tutorials and workshops on the most important data science tools and topics.
Experimentation to Production
Data Science DevOps
Agile Data Science
Data Science Architecture
Runtime Pipelines
Model Monitoring & Auditing
Model Depreciation in Production
Manage Data Science in Your Organization
Collaborative Practices and Tools
Team Management
Data Science Workflows
Data Provenance & Governance
Best Practices & Uses Cases
Cross Industry & Cross Enterprise Challenges
ODSC EAST 2024 - April 23-25th
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