ODSC Webinar Calendar

ODSC’s free webinar series serves to educate our community on the languages, tools, and topics of AI and Data Science

Machine Learning Operationalization (MLOps): Harness the real power of AI

December 7, 2019
11 am – 12:30 pm IST
Click here to register


Add to Calendar
07/12/2019 09:30 PM
America/Los_Angeles
ML Operationalization (MLOps): Harness the real power of AI

Click here for Webinar Access
ODSC Webinar

Nitin Aggarwal
Technical Program Manager, Machine Learning at Google Cloud

ML Operationalization (MLOps): Harness the real power of AI

Recent boom in AI pushed lot of organizations to harness it’s real power and make real impact on the business. Even after having some good ML talent, majority of the AI initiatives ended as a science project. It is very important to productionize and operationalize such solutions with existing systems. There are many ways to do it. Different cloud providers has their own ways to reduce overall burden of building and managing such systems on the businesses. Let’s discuss what are the important factors that we should keep in our mind while productioning any AI/ML system and how the landscape looks like.

Nitin Aggarwal

Nitin is a Technical Program Manager who works with Google Cloud to solve challenging business problems for Google’s strategic customers using cutting edge AI/ML technologies. Nitin believes that responsible and explainable AI can solve real world problems. He has worn many hats during his stint of professional career – Software Engineer, Management Consultant, Data Scientist and ML leader. Nitin holds a degree in engineering and business administration.


Evolutionary AI is the new Deep Learning

December 11, 2019
9 am – 10 am PST
Click here to register


Add to Calendar
11/12/2019 09:00 AM
America/Los_Angeles
Evolutionary AI is the new Deep Learning

Click here for Webinar Access
ODSC Webinar

Babak Hodjat, PhD
Siri Co-Inventor, VP Evolutionary AI, Founder | Cognizant, Sentient Technologies

Evolutionary AI is the new Deep Learning

Today’s AI systems are heavily engineered, data-hungry, and costly to build, as they require immense amounts of processing capacity. Once deployed these ML-based systems, while robust, do not quite keep up with a changing environment, priorities, and needs. Furthermore, while the state-of-the-art in AI in discovering insights from raw data is promising, the decision-making based on these insights is often left to human judgement or rigid predetermined rules. In this talk, we will introduce a complementary technology called Evolutionary AI, which, by virtue of being creative, addresses many of the problems noted above. We will show how Evolutionary AI can automatically design Deep Learning systems, and help generate adaptive decision strategies by constructing prescriptive models.

Babak Hodjat, PhD

Babak Hodjat is VP of Evolutionary AI at Cognizant, and former co-founder and CEO of Sentient, responsible for the core technology behind the world’s largest distributed artificial intelligence system. Babak was also the founder of the world’s first AI-driven hedge-fund, Sentient Investment Management. Babak is a serial entrepreneur, having started a number of Silicon Valley companies as main inventor and technologist. Prior to co-founding Sentient, Babak was senior director of engineering at Sybase iAnywhere, where he led mobile solutions engineering. Prior to Sybase, Babak was co-founder, CTO and board member of Dejima Inc. Babak is the primary inventor of Dejima’s patented, agent-oriented technology applied to intelligent interfaces for mobile and enterprise computing – the technology behind Apple’s Siri. Babak is a published scholar in the fields of Artificial Life, Agent-Oriented Software Engineering, and Distributed Artificial Intelligence, and has 31 granted or pending patents to his name. He is an expert in numerous fields of AI, including natural language processing, machine learning, genetic algorithms, distributed AI, and has founded multiple companies in these areas. Babak holds a PhD in Machine Intelligence from Kyushu University, in Fukuoka, Japan.


Adding Optimization to Your Data Science Analytics Toolkit

December 17, 2019
1 pm – 2 pm EST
Click here to register


Add to Calendar
17/12/2019 10:00 AM
America/Los_Angeles
Adding Optimization to Your Data Science Analytics Toolkit

Click here for Webinar Access
ODSC Webinar

Dr. Gwyneth Butera
Sr. Support Engineer at Gurobi

Dr. Russell Halper
Principal at End-to-End Analytics

Adding Optimization to Your Data Science Analytics Toolkit

Mathematical optimization, specifically Mixed Integer Programming (MIP), is a technology that is used to solve a large variety of problems within multiple industries, including supply chain planning, electrical power generation and distribution, computational finance, sports scheduling, and many more. This powerful technology is complementary to Machine Learning and should be a part of every data scientist’s analytics toolbox. In this webinar, you will learn:
– The basics of optimization and MIP
– How to identify optimization problems within your organization
– When to use MIP vs Artificial Intelligence (AI) when developing a prescriptive analytics solution for your business problem
– How MIP can be used as a complementary technique to Machine Learning
We will present real-world examples of Machine Learning and optimization in action, illustrating the value it can bring to your organization. We will also provide you with next steps on how to get started with optimization as well as available resources.

Dr. Gwyneth Butera

Dr. Butera has over 20 years of optimization software experience. Prior to joining Gurobi Optimization, she worked as a software engineer for IBM ILOG CPLEX Optimization Studio. More recently, she completed an immersive course in Data Science. She has her PhD in Computational and Applied Mathematics from Rice University.

Dr. Russell Halper

Dr. Halper holds a PhD in Applied Mathematics from the University of Maryland. Russell is passionate about developing actionable, pragmatic analytics that align closely with business processes to generate world-class results. He has devoted his career to developing cutting-edge analytics solutions to problems in supply chain, manufacturing, and marketing.


ODSC Europe Warm-Up

Click here to access free recording


Michal Mucha
Senior Data Scientist (independent consultant) at create.ml

Make Beautiful Web Apps from Jupyter Notebooks

Are you a data scientist looking for new and powerful ways to ship data products to users within your organization?
This session offers a crash course in new open source Python, Jupyter and PyData tools to rapidly prototype interactive apps that are as expressive and powerful as any notebook you can build!
Come and learn how to quickly turn Jupyter notebooks – a central element in a data science workflow – into beautiful web apps to share with team members and stakeholders in your organization!

Michal Mucha

Michal leads a successful data science consultancy, delivering strategy and execution on data science, data engineering and ML projects, with clients in retail, transportation, finance, film, and building automation. Beyond technical contributions, he has developed successful approaches to create lasting change in the alignment in organizational collaboration, data literacy, and unlock unrealized human potential that is being stopped by elusive inefficiencies in process and culture.
He holds a Masters degree in Econometrics and Information engineering form Poznan University of Economics. He participated in commercial research projects, including mobile phone data research with published results.


Opening The Black Box - Interpretability In Deep Learning

Click here to access free recording


Matteo Manica, PhD
Research Staff Member at Cognitive Health Care & Life Sciences, IBM Research Zürich

Opening The Black Box - Interpretability In Deep Learning

The recent application of deep neural networks to long-standing problems has brought a break-through in performance and prediction power. However, high accuracy often comes at the price of loss of interpretability, i.e. many of these models are black-boxes that fail to provide explanations on their predictions. This webinar will be an introduction to the ODSC Europe 2019’s training, which will focus on illustrating some of the recent advancements in the field of interpretable artificial intelligence. We will show some common techniques that can be used to explain predictions on pretrained models and that can be used to shed light on their inner mechanisms. The training is aimed to strike the right balance between theoretical input and practical exercises. The session has been designed to provide the participants not only with the theory behind deep learning interpretability, but also to offer a set of frameworks, tools and real-life examples that they can implement in their own projects.

Matteo Manica, PhD

Matteo is a Research Staff Member in Cognitive Health Care and Life Sciences at IBM Research Zürich. He’s currently working on the development of multimodal deep learning models for drug discovery using chemical features and omic data. He also researches in multimodal learning techniques for the analysis of pediatric cancers in a H2020 EU project, iPC, with the aim of creating treatment models for patients. He received his degree in Mathematical Engineering from Politecnico di Milano in 2013. After getting his MSc he worked in a startup, Moxoff spa, as a software engineer and analyst for scientific computing. In 2019 he obtained his doctoral degree at the end of a joint PhD program between IBM Research and the Institute of Molecular Systems Biology, ETH Zürich, with a thesis on multimodal learning approaches for precision medicine.


Accelerating AI-driven Innovation in Your Enterprise

Click here to access free recording


Pallav Agrawal
Director, Data Science at Levi Strauss & Co.

Accelerating AI-driven Innovation in Your Enterprise

The presentation will focus on best practices to develop ML powered applications that can move the needle on business critical KPIs. We will walk through a rapid prototyping framework to develop effective personalization experiences, the mindsets and skills required to execute on an innovation roadmap, how to evaluate and work with vendors that provide ‘AI-powered’ solutions, and how to design experiments to quickly iterate towards a better experience for customers.

Pallav Agrawal

During daytime, Pallav works as a Data Scientist and tries to extract meaningful signals from the noisy world we live in. As the moon rises and evening sets in all bets are off and one might find Pallav on his bike riding through the Berkeley hills in bright colored lycra or performing never-before-scenes of Dramedy with his Improv troupe.

Pallav is a part-time Human Centered Design Thinking coach and has helped non-profits and early-age startups develop clarity on their mission and recognize growth areas. He moved to the Bay Area in 2010 and somehow managed to acquire a Masters in Structural Engineering after spending two years actually learning how to think.

He is an avid follower of Seth Godin, Ken Robinson, and Nicholas Taleb, and is currently looking at ways to explain algorithms through cute, anthropomorphized animals.


Introduction to Deep Learning Models for Computer Vision

Click here to access free recording


Haidar Altaie
Data Scientist at SAS UK&I

Spiros Potamitis
Data Scientist at SAS

Introduction to Deep Learning Models for Computer Vision

In this Webinar, we will discuss the application of DL models using DLPy focusing on Computer Vision. DLPy is a high-level Python API designed to provide an efficient way to apply Deep Learning functionalities using friendly Keras-like APIs to solve Computer Vision, Natural Language Processing, Forecasting, and Speech Processing problems. We explain how DLPy can be applied to data preparation, data processing, model building, assessment and deployment.

This will be a preview of our more in-depth presentation, specifically focused around Multi-Task Deep Learning For Image Tagging, during ODSC Europe in London this November.

Haidar Altaie

Haidar Altaie is a Data Scientist at SAS UK&I. He joined SAS in September 2018 after graduating with a Mathematics and Statistics degree, and is now passionate to integrate Advanced Analytics, Machine Learning, Forecasting and Computer Vision techniques across various industries to enable customer to solve complex real life problem.

Spiros Potamitis

Spiros Potamitis is a data scientist at SAS, a leading software and services provider in advanced analytics. Having acquired an MSc in Information Management from the University of Manchester, Spiros is specialising in the application and implementation of analytics to drive business outcomes. Prior of joining SAS, Spiros has acquired a wealth of predictive modelling experience while working in advanced analytics positions in Credit Risk, Customer Insights and CRM.


Human Machine Learning

Click here to access free recording


Matt Cowell
CEO at QuantHub

Nathan Black
Chief Data Scientist at QuantHub

Human Machine Learning

Could we, as humans, improve the way we learn by applying techniques machines use to learn? From early in the field of AI, researchers have been looking to cognitive psychology for inspiration on how to teach machines to learn. The effectiveness of this approach is evidenced by recent advances in, and growing prevalence of, deep learning. However, we’ve reached a point where machine learning methodologies are deviating from the way humans learn and gaining impressive efficiencies as a result. For humans, this issue is amplified by current findings in cognitive psychology which strongly suggests that many of our long-standing learning methods have been largely misguided. In this webinar, we explore the challenges with common studying practices, contrasting those with methods that machines successfully use to learn, and drawing parallels to recent cognitive psychology research.

Matt Cowell

Matt serves as the CEO at QuantHub, spearheading the drive to help companies overcome the extreme analytics talent shortage and build exceptional data science and engineering teams. Matt has a passion for developing authentic relationships with customers to truly understand what drives them, and then crafting creative solutions to their most critical problems. Prior to joining QuantHub, Matt spent the last 15 years running product and tech at PE-backed companies, including building a product and engineering organization at Daxko to deliver 10x revenue growth, 7 acquisitions, and 3 enormously successful recapitalizations in just 10 years. While at Daxko, Matt led the team to deliver the first machine learning/AI solution to the market, predicting customer membership churn and also propensity to donate.

Nathan Black

Nathan Black is a Data Science Professional and AI Researcher with over 5 years of experience leading and working alongside quant teams to develop cutting-edge, end-to-end data solutions in manufacturing, healthcare, food retail, finance, and education industries. Nathan has a proven track record of using data to help people thrive, assisting organizations in capturing value from data and technology through the deployment of BI, Prescriptive Modeling, and Artificial Intelligence applications.


AI Infrastructure and Supporting the Rise of Data Science

Click here to access free recording


Darrin P. Johnson
Global Director of Solution Architectures at NVIDIA

Matt Miller
Director of Product Marketing at WekaIO

Greg Holick
Director of Technology Alliances at Western Digital

AI Infrastructure and Supporting the Rise of Data Science

The rise of data science is often attributed to the exponential growth of data, whether structured or unstructured. While likely true, it is also true that the supporting AI infrastructure has enabled not only the growth of the data but also has become critical to extracting the value from the data explosion. The industry leaders NVIDIA, WekaIO and Western Digital will each bring their perspective to the importance of AI infrastructure to data science. Whether you are a data scientist, IT professional, or C-level decision maker you will learn how thoughtful AI infrastructure can accelerate your time to insight, time to value and increase profit for your business. You will take away techniques to overcome common challenges and barriers to successful data science in development and in production. Come ready with your questions for the panel to help accelerate your data science.

Darrin P. Johnson

Darrin is the Global Director of Solution Architecture for Enterprise at Nvidia. He and his team lead all DGX, OEM, and storage reference architecture initiatives. Darrin’s experience spans 25 years of leadership in O/S, high performance systems, networking, storage, I/O and most recently AI/Deep Learning technologies with companies such as Cray, SGI, Adaptec, Sun Microsystems, Oracle and now NVIDIA. He is a certified Deep Learning trainer for NVIDIA as well.

Matt Miller

Matt Miller is the Director of Product Marketing for WekaIO, responsible for marketing strategy and positioning. Matt has spent nearly 20 years in the storage industry in both product management and product marketing roles, for companies such as HPE, Nimble Storage, NetApp, Sun Mircosystems and Veritas.

Greg Holick

Greg Holick is a senior technologist with over 15 years of experience in the data storage industry. Throughout his tenure, Greg has engineered software solutions, architected complex storage environments, been the product manager on private cloud solutions, and guided customers and partners on some of the most challenging storage infrastructures in the industry.


Deployment of Strategic AI in the Enterprise: Crossing the Chasm

Click here to access free recording


Fernando Núñez Mendoza
Founder and CEO at fonYou

Deployment of Strategic AI in the Enterprise

The talk “Deployment of Strategic AI in the Enterprise” in the Accelerate AI track of the ODSC West 2019 conference, will argue that the best way to effectively overcome these obstacles is to choose the most critical parts of the business as those in which AI shall be deployed first. This webinar focuses on one key aspect of the strategic AI deployment approach proposed in the talk:  how organizations can cross the chasm that separates AI awareness from AI readiness.

Instead of launching a broad transformational approach to attain AI readiness, it is much more effective to laser focus on critical aspects of the digital value creation network and launch an agile task-force initiative to improve them with AI. By increasingly choosing more complex and ambitious targets, the AI-ready stage should be finally achieved.

Fernando Núñez Mendoza

Fernando Núñez Mendoza, a serial technology entrepreneur and disruptor, is founder, chief executive officer, and chief technology officer of fonYou, a fast-growing international company born in Barcelona, Spain. fonYou’s mission is to build the mobile carrier of the future powered by AI. Before fonYou, he was a management consulting partner at Accenture and Diamond Cluster International helping global telecommunications, technology, and financial services firms embrace the internet and thrive in the brave new digital world. In his earlier career, Fernando worked for the European Space Agency and lectured and performed research in computer engineering and neural networks.

Fernando holds, MSEE and Ph.D. degrees in Electrical and Computer Engineering from the Polytechnic University of Catalonia (Spain), was an invited Visiting Scholar at Purdue University and is alumni of Stanford University Graduate School of Business.


Telling Human Stories With Data

Click here to access free recording


Alan Rutter
Founder of Fire Plus Algebra

Telling Human Stories With Data

Robust data analysis underpins every business decision, public sector project and non-profit initiative. But data in its raw form often fails to convince crucial lay audiences – either due to its complexity, or due to suspicion and mistrust. And you can’t help guide the world in the right direction if you alienate key decision-makers or the public.

This talk, delivered by journalist and data visualization specialist Alan Rutter, will cover an audience-centered approach to visualizing data. It will introduce tried-and-tested techniques for communicating data-driven stories effectively to people from a broad range of backgrounds, and deal with some of the common problems that practitioners encounter.

Alan Rutter

Alan Rutter is the founder of consultancy Fire Plus Algebra, and is a specialist in communicating complex subjects through data visualisation, writing and design. He has worked as a journalist, product owner and trainer for brands and organisations including Guardian Masterclasses, WIRED, Time Out,the Home Office, the Biotechnology and Biological Sciences Research Council and Liverpool School of Tropical Medicine.


Dumb & Dumber vs Ocean’s 11: Tackling evolving, sophisticated fraud with AI

Click here to access free recording


Sathya Chandran, PhD
Security Research Scientist at DataVisor

Dumb & Dumber vs Ocean’s 11: Tackling evolving, sophisticated fraud with AI

Sophisticated fraud attacks that are extensively planned, hard to detect, and highly scalable are becoming the new normal for online platforms. Learn more about the spectrum of fraud attacks – from “dumb & dumber” to “ocean’s 11″– and why Unsupervised Machine Learning is the key to detecting attacks before they inflict damage.

Sathya Chandran, PhD

Sathya is an expert in applying big data and unsupervised machine learning to fraud detection, specializing in the financial, e-commerce, social, and gaming industries. Sathya holds PhD in CS from the University of South Florida and has previously worked at HP Labs and Honeywell.

Free access to ODSC talks and content is available at our

AI Learning Accelerator

ODSC EAST | Boston

– April 30th – May 3rd, 2019 –

The World’s Largest Applied Data Science Conference

ODSC EUROPE | London

– Nov 19th – 22nd, 2019 –

Europe’s Fastest Growing Data Science Community

ODSC WEST | San Francisco

– Oct 29th – Nov 1st, 2019 –

The World’s Largest Applied Data Science Conference

Accelerate AI

Business Conference

The Accelerate AI conference series is where executives and business professionals meet the best and brightest innovators in AI and Data Science. The conference brings together top industry executives and CxOs that will help you understand how AI and data science can transform your business.

Accelerate AI East | Boston

– April 30th – May 1st, 2019 –

The ODSC summit on accelerating your business growth with AI

Accelerate AI Europe | London 

– Nov 19th – 20th, 2019 –

The ODSC summit on accelerating your business growth with AI

Accelerate AI West | San Francisco 

– Oct 29th – 30th, 2019 –

The ODSC summit on accelerating your business growth with AI