Full Machine Learning Week 7-Track Agenda 2020

Predictive Analytics World

May 31-June 4, 2020


This page shows the full 7-track agenda for the five co-located conferences at Machine Learning Week. A Machine Learning Week Ticket is required for full access. To view the agenda for one individual conference, click here: PAW Business, PAW Financial, PAW Healthcare, PAW Industry 4.0, or Deep Learning World.

Session Levels:

Blue circle sessions are for All Levels
Red triangle sessions are Expert/Practitioner Level

All times are Pacific Daylight Time (PDT/UTC-7)

Pre-Conference Workshops - Sunday, May 31st, 2020

8:30 am
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one day workshop reviews major big data success stories that have transformed businesses and created new markets. Click workshop title above for the fully detailed description. 

Session description
Instructors
Vladimir Barash
Director
Graphika
Marc Smith
Chief Social Scientist
Connected Action Consulting Group
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Gain experience driving R for predictive modeling across real examples and data sets. Survey the pertinent modeling packages.  Click workshop title above for the fully detailed description. 

Session description
Instructor
Robert MuenchenUniversity of Tennessee
Manager of Research Computing Support
University of Tennessee
4:30 pm
End of Sunday Pre-Conference Training Workshops
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Pre-Conference Workshops - Monday, June 1st, 2020

8:30 am
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning). Click workshop title above for the fully detailed description. 

Session description
Instructor
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Python leads as a top machine learning solution – thanks largely to its extensive battery of powerful open source machine learning libraries. It’s also one of the most important, powerful programming languages in general. Click workshop title above for the fully detailed description. 

Session description
Instructor
Clinton BrownleyWhatsApp
Data Scientist
WhatsApp
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Machine learning improves operations only when its predictive models are deployed, integrated and acted upon – that is, only when you operationalize it.  Click workshop title above for the fully detailed description. 

Session description
Instructor
James TaylorDecision Management Solutions
CEO
Decision Management Solutions
4:30 pm
End of Monday Pre-Conference Training Workshops
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Day 1 - Tuesday, June 2nd, 2020

8:00 am
8:10 am
PAW Business MACHINE LEARNING WEEK KEYNOTE
Lessons from: Microsoft
Speaker
Mohammad Shokoohi-YektaMicrosoft
Senior Data Scientist
Microsoft
PAW Financial MACHINE LEARNING WEEK KEYNOTE
Lessons from: Microsoft
Speaker
Mohammad Shokoohi-YektaMicrosoft
Senior Data Scientist
Microsoft
PAW Healthcare MACHINE LEARNING WEEK KEYNOTE
Lessons from: Microsoft
Speaker
Mohammad Shokoohi-YektaMicrosoft
Senior Data Scientist
Microsoft
PAW Industry 4.0 MACHINE LEARNING WEEK KEYNOTE
Lessons from: Microsoft
Speaker
Mohammad Shokoohi-YektaMicrosoft
Senior Data Scientist
Microsoft
Deep Learning World MACHINE LEARNING WEEK KEYNOTE
Lessons from: Microsoft
Speaker
Mohammad Shokoohi-YektaMicrosoft
Senior Data Scientist
Microsoft
8:35 am
PAW Business MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
PAW Financial MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
PAW Healthcare MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
PAW Industry 4.0 MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
Deep Learning World MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
9:20 am
Break
Break
Break
Break
Break
9:30 am
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Track Co-Chair: James Taylor
Digital decisioning
9:30 am - 9:50 am
Speaker
James TaylorDecision Management Solutions
CEO
Decision Management Solutions
Project leadership
9:55 am - 10:15 am
Lessons from: Cisco
Speaker
Jennifer RedmonCisco
Chief Data Evangelist
Cisco Systems, Inc
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Model explainability/interpretability
Speaker
Dean AbbottSmarterHQ
Co-Founder and Chief Data Scientist
SmarterHQ
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Cross-enterprise applications
9:30 am - 9:50 am
Case study: Facebook
Speaker
Mohamed FawzyFacebook
Senior Software Engineering Lead - AI Infra
Facebook
Cross-enterprise applications
9:55 am - 10:15 am
Case study: Walmart Labs and Sam's Club
Speaker
Kunal DesaiWalmart eCommerce
Director of Product Management
Walmart eCommerce
PAW Financial
Insurance applications
9:30 am - 9:50 am
Case study: ESIS
Speaker
Keith HigdonESIS
President
ESIS
Risk management
9:55 am - 10:15 am
Case study: Swiss Reinsurance Company
Speaker
Christian ElsasserSwiss Re
Senior Risk Analytics Manager - P&C Analytics
Swiss Reinsurance Company Ltd
PAW Healthcare
Case Study: COVID-19 Mobility and Data Analysis
Speaker
Mike ThurberElder Research
Lead Data Scientist
Elder Research
PAW Industry 4.0 KEYNOTE
Speaker
Terry MillerSiemens
Global Digital Strategy and Business Development
Siemens
Deep Learning World KEYNOTE
Case Study: Standard Cognition
Speaker
Sean HendryxStandard Cognition
Machine Learning Engineer
Standard Cognition
10:15 am
Break
Break
Break
Break
Break
10:25 am
PAW Business Track 1 - BUSINESS - Operationalization, management and best practices
Gaining stakeholder buy-in
10:25 am - 10:45 am
Lessons from: FedEx
Speaker
Clayton ClouseFedEx
Senior Data Scientist
FedEx
Pitfalls and best practices
10:50 am - 11:10 am
Speaker
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Machine learning automation
Case study: Facebook
Speaker
Clinton BrownleyWhatsApp
Data Scientist
WhatsApp
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Analytics in retail
10:25 am - 10:45 am
Case study: Walmart
Speaker
Hamza FarooqWalmart Labs
Principal Data Scientist
Walmart Labs
Marketing applications; reinforcement learning
10:50 am - 11:10 am
Case study: Samsung
Speaker
Venkata PakkalaSamsung
Staff Data Scientist
Samsung
PAW Financial
Long-term risk management
10:25 am - 10:45 am
Case study: Safety National Casualty
Speakers
Carrie Lu Ph.D.Safety National Casualty Corporation
Senior Data Scientist
Safety National Casualty Corporation
William WIlkinsSafety National Casualty Corporation
Chief Risk and Data Analytics Officer
Safety National Casualty Corporation
Real-time architecture (streaming analytics)
10:50 am - 11:10 am
Case study: ING
Speaker
Bas GeerdinkAizonic
CTO
Aizonic
PAW Healthcare
Case Study: Southeastern Health Partners (SEHP)
Speaker
Michael Gold
Principal
Front Health
PAW Industry 4.0
Speaker
Rajagopalan ChandrasekharanGE Global Research
Senior Engineer
General Electric
Deep Learning World Large Scale Deployed Deep Learning
Speakers
Justin Chien
Senior Data Scientist
6sense
Rohit Kewalramani
Data Scientist
6Sense Insights Inc.
11:10 am
Break
Break
Break
Break
Break
11:20 am
PAW Business SPECIAL PLENARY SESSION
Speaker
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
PAW Financial KEYNOTE
Lessons from: Manulife
Speaker
Richard LeeManulife
Director of Data Science, US EOIT Advanced Analytics & AI
Manulife
PAW Healthcare KEYNOTE
Speaker
Taylor DavisKLAS
VP of Research
KLAS
PAW Industry 4.0 SPECIAL PLENARY SESSION
Speaker
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
Deep Learning World Large Scale Deployed Deep Learning
Case Study: Genesys Telecommunication Labs
Speaker
Anthony AlfordGenesys
Lead Software Engineer
Genesys
12:05 pm
PAW Business
Sponsored by
DataRobot
Speaker
Ari KaplanDataRobot
Director, Marketing
DataRobot
PAW Financial
Sponsored by
DataRobot
Speaker
Ari KaplanDataRobot
Director, Marketing
DataRobot
PAW Healthcare
Sponsored by
DataRobot
Speaker
Ari KaplanDataRobot
Director, Marketing
DataRobot
PAW Industry 4.0
Sponsored by
DataRobot
Speaker
Ari KaplanDataRobot
Director, Marketing
DataRobot
Deep Learning World
Sponsored by
DataRobot
Speaker
Ari KaplanDataRobot
Director, Marketing
DataRobot
12:25 pm
Break
Break
Break
Break
Break
12:45 pm
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Cross-enterprise management
12:45 pm - 1:05 pm
Lessons from: Google
Speaker
Richard DuttonGoogle
Head of Machine Learning for Corporate Engineering
Google
Cross-enterprise management
1:10 pm -1:30 pm
Lessons from: LinkedIn
Speakers
Sunil AyyapanLinkedIn
Senior Technical Program Manager
LinkedIn
Priyanka GaribaLinkedIn
Head of Artificial Intelligence Technical Program Management
LinkedIn
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Uplift modeling, marketing analytics
Case study: Sam's Club
Speaker
Markus DmytrzakSam’s Club
Director, Advanced Analytics and Decision Sciences
Sam's Club
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Product recommendations, analytics in the entertainment industry
12:45 pm - 1:05 pm
Case study: Fadango
Speaker
Reeto MookherjeeFandango
Vice President, Data, Analytics and Business Intelligence
Fandango
ML in AdTech
1:10 pm - 1:30 pm
Case study: Leading Ad Tech SSP
Speaker
Allen YuLineate
Director of AI
Lineate
PAW Financial
Operationalization
12:45 pm - 1:05 pm
Case study: A leading financial services firm
Speaker
Naveed Asem
Chief Data Officer
Guaranteed Rate
Transaction analytics, ML for audit support
1:10 pm - 1:30 pm
Speaker
Leslie BarrettBloomberg
Senior Software Engineer
Bloomberg LP
PAW Healthcare
Using AI to Save Lives
Speaker
Vickie RiceCareATC, Inc.
Vice President of Innovative Strategies
CareATC, Inc.
Deep Learning World Techniques and Results
Case Study: Shell
Speaker
Mohamed SidahmedShell Oil Company
Machine Learning and AI Manager
Shell
1:30 pm
Break
Break
Break
Break
Break
1:40 pm
PAW Business Track 1 - BUSINESS - Operationalization, management and best practices
Analytics strategy
1:40 pm - 2:00 pm
Lessons from: Freewheel, A Comcast Company
Speaker
Bob BressComcast Cable
Vice President of Analytics & Business Intelligence
Freewheel, A Comcast Company
Project leadership
2:05 pm - 2:25 pm
Speaker
Robert Grossman
Managing Partner
Analytic Strategy Partners LLC
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Uplift modeling, marketing analytics
Case study: CVS
Speaker
John GaoWorkHuman
Senior Manager
WorkHuman
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Cybersecurity applications
1:40pm - 2:00 pm
Case study: McAfee
Speaker
Celeste FralickMcAfee
Chief Data Scientist, Senior Principal Engineer
McAfee
Building data science capacity
2:05 pm - 2:25 pm
Case study: Canada Energy Regulator
Speaker
Shingai ManjengwaFireside Analytics
Chief Executive Officer
Fireside Analytics Inc.
PAW Financial
Algorithmic trading
Case study: Bloomberg
Speaker
Chakri CherukuriBloomberg
Senior Quantitative Researcher
Bloomberg
PAW Healthcare
Speaker
John Ainsworth
Senior Data Scientist
University of Virginia Health System
PAW Industry 4.0 KEYNOTE
Speaker
Andrei KhurshudovCaterpillar
Director, Advanced Analytics
Caterpillar Digital
Deep Learning World Large Scale Deployed Deep Learning
Case study: Facebook
Speaker
Manoj Kumar KrishnanFacebook
Software Engineer and Tech Lead
Facebook
2:25 pm
Break
Break
Break
Break
Break
2:35 pm
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Management
2:35 pm - 2:55 pm
Lessons from: Xerox PARC
Speaker
Mark CramerPARC, a Xerox Company
Applied AI Product Management
Xerox at PARC
Analytics culture and leadership
3:00 pm - 3:20 pm
Lessons from: AppFolio
Speaker
Michael GaltressAppfolio
Director, Business Analytics & Insights
Appfolio
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Uplift modeling, marketing analytics
Lessons from: Fidelity
Speaker
Victor LoFidelity Investments
AI and Data Science Center of Excellence Leader, Workplace Investing
Fidelity Investments
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Customer feedback, text analytics
Case study: Google
Speaker
Peter GrabowskiGoogle
Software Engineering Manager
Google
PAW Financial
Collections; advanced methods
Case study: Wells Fargo
Speaker
Connor Jennings Ph.D.Wells Fargo
Senior Data Scientist, AI Model Development Center of Excellence
Wells Fargo
PAW Healthcare
Case Study: Blood Supply Management and Forecasting
Speakers
Kelley CountsOneBlood
Data Scientist
OneBlood
Karl RexerRexer Analytics
President
Rexer Analytics
Deep Learning World Large Scale Deployed Deep Learning
Case study: Nauto
Speakers
Piyush ChandraNauto
AI Product Management
Nauto
Shweta ShrivastavaNauto
Chief Product Officer
Nauto
3:20 pm
End of first Conference Day
End of first Conference Day
End of first Conference Day
End of first Conference Day
Deep Learning World Techniques and Results
Case study: REI Systems
Speakers
Zulfiqar AhmedREI Systems
Associate Data Analyst
REI Systems
Nikolay SorokinREI Systems
Data Scientist
REI Systems
4:05 pm
 
 
 
 
Deep Learning World Techniques and Results
Case study: Facebook
Speaker
Jason GauciFacebook
Engineering Manager
Facebook
4:50 pm
 
 
 
 
 
Day 2 - Wednesday, June 3rd, 2020

8:00 am
8:10 am
PAW Financial KEYNOTE
Lessons from: Fidelity
Speaker
Victor LoFidelity Investments
AI and Data Science Center of Excellence Leader, Workplace Investing
Fidelity Investments
PAW Healthcare KEYNOTE
Speaker
Rick HintonValerius
Founder & CEO
Valerius
Deep Learning World KEYNOTE
Case Study: The Vanguard Group
Speaker
Vishal HawaThe Vanguard Group
Principal Scientist
The Vanguard Group
8:45 am
 
 
 
8:55 am
PAW Business
Sponsored by
Altair
PAW Financial
Sponsored by
Trisotech
PAW Healthcare
Sponsored by
DataRobot
Speaker
Matt MarzilloDataRobot
Customer Facing Data Scientist
DataRobot
PAW Industry 4.0
Sponsored by
Altair
Deep Learning World
9:15 am
Break
Break
Break
Break
Break
9:25 am
PAW Business Track 1 - BUSINESS - Operationalization, management and best practices
Track Co-Chair: James Taylor
Speaker
Michael SimonCIA
Chief of Analytics
CIA
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Model explainability
Case study: Paychex
Speakers
Val CareyPaychex
Data Scientist
Paychex
Satish PrabhuPaychex
Data Scientist
Paychex
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
ML for social good
9:25 am - 9:45 am
Speaker
Anasse Bari Ph.D.New York University
Clinical Assistant Professor of Computer Science
New York University
PAW Financial
Algorithmic trading
Case study: Goldman Sachs
Speakers
Andreas PetridesGoldman Sachs
Quantitative Researcher
Goldman Sachs
Michael SteliarosGoldman Sachs
Managing Director
Goldman Sachs
PAW Healthcare
Case Study: NorthShore University Health System
Speaker
Daniel Chertok PhDNorthShore University HealthSystem
Sr. Data Scientist
NorthShore University HealthSystem
PAW Industry 4.0
Speaker
Samira GolsefidPayPal
Principal Data Scientist
PayPal Inc.
Deep Learning World Techniques and Results
Case Study: Facebook
Speaker
Geeta ChauhanFacebook
AI Partnerships
Facebook
10:10 am
Break
Break
Break
Break
Break
10:20 am
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Algorithmic fairness; ethics
10:20 am - 10:40 am
Speaker
Natalia ModjeskaInfo-Tech Research Group
Director, Research, DnA (Data & Analytics)
Info-Tech Research Group
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Modeling methods
Speaker
Dan Steinberg Ph.D.
CEO
Choice Analytics
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Churn modeling
10:20 am - 10:40 am
Speaker
Gilad BarashDstillery
VP of Analytics
Dstillery
Churn modeling
10:45 am - 11:05 am
Case study: Wix
Speaker
Gil ReichWix
Data Developer
Wix
PAW Financial
The cyborg effect
10:20 am - 10:40 am
Speaker
Richard Boire
President
Boire Analytics
Financial applications; transactional data
10:45 am - 11:05 am
Case study: Visa
Speaker
Abhishek Joshi ‘AJ’Visa
Senior Director
Visa Consulting & Analytics
PAW Healthcare
Cancer Prediction
Speaker
Bob NisbetUniversity of California, Irvine Extension
Instructor
University of California, Irvine
Deep Learning World Large Scale Deployed Deep Learning
Case Study: eBay
Speaker
Kumaresan ManickavelueBay
Sr. Product Manager, NLP
eBay
11:05 am
Break
Break
Break
Break
Break
11:15 am
PAW Business KEYNOTE
Lessons from: Kennesaw State University
Speaker
Jennifer Lewis PriestleyKennesaw State University
Professor of Applied Statistics and Data Science
Kennesaw State University
PAW Financial
Client transaction optimization
Case study: Charles Schwab
Speaker
Jodi BlombergCharles Schwab
Managing Director, Enterprise Analytics
Charles Schwab
PAW Healthcare
Deep Learning World Large Scale Deployment
Case study: Walmart
Speaker
Le ZhangWalmart
Data Scientist
Walmart
12:10 pm
Break
Break
Break
Break
Deep Learning World Techniques and Results
Case Study: eBay Corporation
Speaker
Navid ImanieBay
Applied Researcher
eBay
Break
12:30 pm
PAW Business
Moderator
James TaylorDecision Management Solutions
CEO
Decision Management Solutions
Panelists
Bill FranksInternational Institute For Analytics
Chief Analytics Officer
International Institute For Analytics
Natalia ModjeskaInfo-Tech Research Group
Director, Research, DnA (Data & Analytics)
Info-Tech Research Group
Tom WardenEMPLOYERS
SVP, Chief Data and Analytics Officer
EMPLOYERS
PAW Financial
Moderator
Mei Najim
CSPA, Founder and Lead Data Scientist
Advanced Analytics Consulting Services, LLC
PAW Healthcare
Case Study: West African Ebola Outbreak
Speaker
Colleen Farrelly
Co-Founder & Chief Scientist
Quantopo LLC
Break
1:15 pm
Break
Break
Break
Break
Deep Learning World Techniques and Results
Case Study: Verizon
Speaker
Shams ZamanVerizon
Principal Data Scientist
Verizon
1:25 pm
PAW Business Track 1 - BUSINESS - Operationalization, management and best practices
Industry/University Partnerships
1:25 pm - 1:45 pm
Lessons from: Hanesbrand
Speakers
Haya AjjanElon University
Associate Professor of MIS, Director of the Center for Organizational Analytics,
Elon University
Ben Martin Ph.D.Hanes
Chief Data Analytics Officer
Hanesbrands Inc
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Data engineering
Case study: Google
Speaker
Karl WeinmeisterGoogle
Developer Advocacy Manager
Google
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Workforce analytics
1:25 pm - 1:45 pm
Case study: Bristol-Myers Squibb
Speakers
Jason FelicianoBristol-Myers Squibb
Associate Director of HR Analytics
Bristol-Myers Squibb
Emma VazirabadiBristol-Myers Squibb
Associate Director of People Insights & HR Analytics
Bristol-Myers Squibb
Workforce analytics
1:50 pm - 2:10 pm
Case study: Mercer
Speaker
Haig NalbantianMercer
Senior Partner, Co-leader Mercer Workforce Sciences Institute
Mercer
PAW Financial
Portfolio analytics; data sources
Speaker
Anasse Bari Ph.D.New York University
Clinical Assistant Professor of Computer Science
New York University
PAW Healthcare
1:25pm - 1:45pm
Addressing Bias
Speaker
Zeydy Ortiz
CEO
DataCrunch Lab
1:50pm - 2:10pm
Speaker
Ali Boolani
Associate Professor
Clarkson University
Break
2:10 pm
Break
Break
Break
Break
Deep Learning World Techniques and Results
Case Study: Google
Speaker
Patrick MillerGoogle
Software Engineering Manager
Google
2:20 pm
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Best practices for operationalization
Lessons from: Hitachi Vantara Federal
Speaker
Pragyansmita NayakHitachi Vantara Federal (HVF)
Chief Data Scientist
Hitachi Vantara Federal (HVF)
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Modeling methods
2:20 pm - 2:40 pm
Case study: Cisco
Speaker
Kumaran PonnambalamCisco
Analytics Architect
Cisco Systems, Inc
Machine learning automation
2:45 pm - 3:05 pm
Case study: Google
Speaker
Eugene KirpichovGoogle
Software Engineer, Research and Machine Intelligence
Google
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Consumer reimbursement claims
2:20 pm - 2:40 pm
Case study: GIVT (EU flight claims)
Speaker
Piotr Wygocki Ph.D.MIM Solutions
​Co-founder
MIM Solutions
Supply chain management
2:45 pm - 3:05 pm
Case study: ChannelAdvisor
Speaker
Kevin FeaselChannelAdvisor
Engineering Manager, Predictive Analytics
ChannelAdvisor
PAW Financial
Credit scoring
Case study: Vision Fund International
Speaker
Aric LaBarrInstitute for Advanced Analytics at NC State University
Associate Professor of Analytics
Institute for Advanced Analytics at NC State University
PAW Healthcare
Case Study: Capital District Physicians’ Health Plan
Speaker
Matthew PietrzykowskiCapital District Physicians’ Health Plan
Principal Data Scientist
Capital District Physicians' Health Plan
PAW Industry 4.0
Speaker
Rohit Kewalramani
Data Scientist
6Sense Insights Inc.
 
3:05 pm
End of second Conference Day
End of second Conference Day
End of second Conference Day
End of second Conference Day
Deep Learning World Techniques and Results
Case study: DeepScale (a Tesla company)
Speaker
Ilke DemirDeepScale (a Tesla company)
Senior Research Scientist
DeepScale (a Tesla company)
3:50 pm
 
 
 
 
End of Second Conference Day
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Post-Conference Workshops - Thursday, June 4th, 2020

8:30 am
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one-day session reveals the subtle mistakes analytics practitioners often make when facing a new challenge (the “deadly dozen”), and clearly explains the advanced methods seasoned experts use to avoid those pitfalls and build accurate and reliable models.  Click workshop title above for the fully detailed description.

Session description
Instructor
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Gain the power to extract signals from big data on your own, without relying on data engineers and Hadoop specialists. Click workshop title above for the fully detailed description.

Session description
Instructor
James Casaletto
PhD Candidate
UC Santa Cruz Genomics Institute and former Senior Solutions Architect, MapR
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This workshop dives into the key ensemble approaches, including Bagging, Random Forests, and Stochastic Gradient Boosting. Click workshop title above for the fully detailed description.

Session description
Instructor
Dean AbbottSmarterHQ
Co-Founder and Chief Data Scientist
SmarterHQ
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

During this workshop, you will gain hands-on experience deploying deep learning on Google’s TPUs (Tensor Processing Units) at this one-day workshop, scheduled the day immediately after the Deep Learning World and Predictive Analytics World two-day conferences.  Click workshop title above for the fully detailed description.

Session description
Instructor
Drew HodunGoogle
Machine Learning Specialist - Google Cloud
Google
4:30 pm
End of Post-Conference Training Workshops
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