Convergence Vancouver

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The Westin Bayshore, Vancouver

1601 Bayshore Drive

Vancouver, BC V6G 2V4

Canada

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CONVERGENCE VANCOUVER: A full-day seminar focused on deploying ML & AI for digital transformation.

Did you know that 90% of an organization’s success with machine learning and artificial intelligence has more to do with logistics than it does mathematical brilliance? As a result, the solutions added to handle machine learning frameworks often only make the problems more profound.

Join MapR Technologies in the discussion on the value of exploiting data assets via machine learning and artificial intelligence to drive business performance and transformation.

MapR Convergence offers attendees opportunities to network and interact with industry experts, MapR customers and partners. Register TODAY to be part of the discussion as we explore how the infrastructure of a converged data platform directly affects a company’s machine learning and artificial intelligence capabilities.

We look forward to seeing you in Vancouver!




AGENDA

8:00-9:00 am Registration and Networking Breakfast

9:00-9:05 am Introductions and Welcome

9:05-9:50 am "A Whole New Way to Think About Your Next-Gen Applications," Tom Fisher, EVP and CTO at MapR Technologies

9:50-10:25 am "Modernizing the Lending Platform: Data-Driven Decisioning," Brad Anderson, Head of Data Platform at Kabbage

10:25- 11:00 am Networking Break

11:00 -11:45 am "Machine Learning Logistics," Ted Dunning PhD, Chief Application Architect at MapR Technologies

11:45 - 12:25 pm 'Lightning Round' Interactive Discussion

12:25 -1:25 pm Lunch

1:25- 2:00 pm "The Role of Streaming in a Global Data Fabric," Ellen Friedman PhD, Principal Technologist at MapR Technologies and O'Reilly author

2:00-2: 45 pm "Real World Use Cases: Practical Tips for What You Can Do " Ian Downard, Senior Technical Engineer at MapR Technologies and Ted Dunning PhD, Chief Application Architect at MapR Technologies

2:45-3:00 pm Closing wrap-up

3:00 -3:20 pm Complimentary Book Signing: Machine Learning Logistics by Ted Dunning and Ellen Friedman

3:00 - 4:45 pm Meet and Greet the Experts Networking Reception





Featured Speakers



Tom Fisher, EVP and CTO at MapR Technologies

As CTO, Tom works with enterprise customers to ensure they take full advantage of MapR technology. He also leads initiatives to advance the company’s innovation agenda globally.

Tom was previously with Oracle, where he was a senior executive in engineering and operations for over five years, supporting the company’s top 40 cloud customers globally. He was also Oracle’s senior vice president and CIO for global commercial cloud services, focusing on improving service delivery through automation and direct action with customers. Prior to Oracle, Tom served as CIO and vice president of cloud computing at SuccessFactors (now SAP), where he ran cloud operations as well as emerging technologies in product engineering. Additionally, Tom led technology teams at Qualcomm as CIO of CDMA technologies and with eBay Inc. where he was vice president and acting CTO.





Ted Dunning PhD, Chief Application Architect at MapR Technologies

Ted Dunning is Chief Application Architect at MapR and has years of experience with machine learning and other big data solutions across a range of sectors. Ted was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems. He built fraud detection systems for ID Analytics (later purchased by LifeLock) and he has 24 patents issued to date plus a dozen pending. Ted has a PhD in computing science from the University of Sheffield and is active with open source projects as committer, PMC member, mentor and currently serving as a board member for the Apache Software Foundation. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting.




Ellen Friedman PhD, Principal Technologist at MapR Technologies and O'Reilly author

Ellen Friedman (@Ellen Friedman) is a solutions consultant, scientist, author and a committer on Apache Drill and Apache Mahout projects. With a PhD in biochemistry and having written and spoken on a variety of scientific and computing topics, she is an experienced communicator. Her books include Introduction to Apache Flink; Streaming Architecture; the Practical Machine Learning series and Time Series Databases, plus data report “Data Where You Want It: Geo-Distribution of Big Data and Analytics”, all from O'Reilly. Ellen has been an invited speaker at Strata London, the Nike Tech Talks in Portland, Data Day Seattle, Berlin Buzzwords, Philly ETE conference and a keynote speaker at Big Data London and at NoSQL Matters (Barcelona). Beyond work with big data, she enjoys painting and is co-author of a book of magic-themed cartoons, A Rabbit Under the Hat.




Brad Anderson, Head of Data Platform at Kabbage

Brad Anderson is Head of Data at Kabbage, the only fully-automated online lending company. Before joining Kabbage in 2016, Anderson was VP Big Data Informatics at Liaison Technologies, constructing the Alloy™ Data Management Platform for healthcare and life sciences, among other verticals. He has also founded or co-founded four technology companies across a variety of industries, all employing big data technologies. Past companies include MapR Technologies, Ericsson and Cloudant, and he has many contributions to distributed systems open-source projects, including Hadoop, HBase, CouchDB, and Titan.




Featured Sessions


A Whole New Way to Think About Your Next-Gen Applications

Tom Fisher, EVP and CTO at MapR Technologies

If you’re struggling to build applications that harness all of your data, you also likely find it a challenge to gather the data in real time, build intelligent models, and reliably deploy them at scale in production as part of mission-critical business applications. Classic relational databases are unable to handle modern data intensive workloads, and NoSQL databases can’t provide the breadth of capabilities required for diverse enterprise applications.

Tom Fisher explains how customers using a converged data platform are succeeding at creating breakthrough new apps for the enterprise. Converged capabilities ranging from cloud-scale data stores to powerful databases and integrated persisted streaming create new possibilities for enterprise developers looking to architect, develop, and deploy applications that were impossible until now.



Machine Learning Logistics

Ted Dunning PhD, Chief Application Architect at MapR Technologies

As is true in many aspects of life, success with machine learning or artificial intelligence often has more to do with good housekeeping than with mathematical brilliance. The dirty little secret of the entire field is 90% of the effort goes into the logistics rather than the machine learning. That 90% comes from many things such as the need to stage and deploy multiple versions of each model, from the need to carefully collect and curate updated training data and from the need to monitor model performance. Lately we have added scale, speed and the need to handle multiple machine learning frameworks at the same time to make the problem more difficult.


In my own experience and from talking with other people who have deployed production models, I think that there is a common architecture that could make this a lot easier. This new architecture should capitalize on recent ideas about streaming micro-services, containerization, and orchestration.


This talk will cover the basic development of a rendezvous architecture and it solves many of the problems involved in continuous deployment of machine learning models. I will cover techniques for model deployment, management, monitoring and comparison. After the talk, there will be an open discussion about where this effort should go from here.



The Role of Streaming in a Global Data Fabric

Ellen Friedman PhD, Principal Technologist at MapR Technologies and O'Reilly author

Our best insights are drawn when our data and analyses fit the way life happens – and generally life doesn’t happen in batches. Many companies are already discovering the advantages of a comprehensive streaming-first architecture that go far beyond just low latency applications. One of the advantages of stream-first design is that it makes it much easier to build a global data fabric, giving you have data where you want it and computation where you need it, across geo-distributed locations from edge computing to multiple data centers, on premises or in cloud. This presentation examines the technical requirements needed to build a global data fabric, how a data fabric provides the flexibility of microservices and how streaming is a key aspect. We will see how these design choices play out to advantage in specific use cases, including how they make it easier to handle the logistics of machine learning. Finally, we’ll take a look at how a DataOps style of work let’s you take full advantage of streaming and a global data fabric.



Modernizing the Lending Platform: Data-Driven Decisioning

Brad Anderson, Head of Data Platform, Kabbage

Banking systems, and in particular lending platforms, need to begin leveraging recent advancements in machine learning, deep learning, and artificial intelligence. To be successful, they need to ingest much more data than they have in the past. Ingesting these data and serving them to new underwriting and decisioning algorithms, as well as to the rest of the organization for analytics, require changes in data architectures. We will discuss these changes to architecture, the building blocks required for success, and FinTech use cases enabled with these advancements.





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Date and time

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The Westin Bayshore, Vancouver

1601 Bayshore Drive

Vancouver, BC V6G 2V4

Canada

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Organizer MapR Technologies

Organizer of Convergence Vancouver

The Industry's Leading Data Platform for AI and Analytics

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