SEMINAR: Enterprise Machine Learning & Deep Learning

Monday, December 3 | 1:15 – 5:00

           Hosted By

Learn about your AI options, who are the players, and what are the key technologies. Hear from world-class machine learning experts at Fortune 500 businesses that are developing innovative enterprise applications today.

This half day seminar provides a comprehensive introduction to attendees on the entire machine learning (ML) industry, including the different players, options, and technologies. A particular focus will be on deep learning (DL) and reinforcement learning (RL) to enable attendees to gain in-depth concepts of DL, which revolutionizes data science tasks such as image recognition, speech analysis or time series prediction as well as RL.

Participants will:

  • Gain a thorough overview of today’s ML, DL and RL market,
  • Learn when to use machine learning and when to use deep learning and reinforcement learning,
  • Gain knowledge about how and where to get and use the right type of data for different applications,
  • Learn where in your organization you can find the best type of applications,
  • Learn what type of approach your company should use in terms of building your own team and/or working with third party service and software providers, and
  • What options are now available in the cloud.

Attendees will also gain a deep sense of understanding of what steps to take next and will be well equipped to accelerate their internal business AI initiatives.

1:15 State-of-the-Practice of Machine Learning in the Enterprise

Kanty_Milczek_JanJan Kanty Milczek, Senior Data Scientist,

Machine learning is often described as the technology of the future, but it is also the technology of the present. In this talk, we describe the applications of both simple and complicated algorithms to earn money or solve problems here and now. This comprehensive enterprise-level introduction to machine learning and deep learning technology includes approaches such as:

  • Reducing person-hours in data collection
  • Optimizing power consumption
  • Visual risk management (forest fire hazard, intrusions, quality assurance, etc.)

1:45 The What, Why, and How of Deep Learning & Reinforcement Learning

Godula_PawelPawel Godula, Director of Customer Analytics,

How does an enterprise determine which applications may best benefit from using machine learning and deep learning? This three-part presentation describes use cases and statistics from different industries leveraging these technologies in innovative ways. We will answer questions such as:

  • Neural networks: what is the current state of deep learning and what are the prospects for its development? What is reinforcement learning and why has it created such enormous expectations?
  • Why are AI solutions beneficial for a company?
  • What can you expect from AI? Competitive advantage, business growth and cost reductions.
2:20 Networking Refreshment Break

2:50 PANEL: Deep Learning in the Enterprise – Opportunities and Challenges

This strategic overview of the deep learning market is provided by’s experts and professionals from large enterprises who have deployed deep learning applications at their company. Hear from world class heads of data science and innovation departments for major U.S. companies. Learn how the largest organizations use machine learning techniques, how deep learning is disrupting their industries, and critical lessons learned in deploying enterprise class machine learning applications. After the panel, everyone is invited to take part in the discussion and ask questions about practical applications of AI technology.

The panelists will address:

  • How to know if your business needs machine learning?
  • How to construct an effective plan for a successful machine learning deployment project?
  • What are new business sectors where deep learning solutions are not widely adopted yet, but which have potential?
  • What would you recognize as the most promising trends and technologies for the future?

Bogucki_RobertRobert Bogucki, Chief Technology Officer,

Osterreicher_PawełPawel Osterreicher, Director of Strategy & Business Development,

Mainak Mazumdar, Chief Researcher Officer, Nielsen


Jeremy Wenxiao Gu, Senior Data Scientist, Uber


Danielle Ciofani, Director of Data Strategy & Alliances, Broad Institute of MIT

3:30 AI, Deep Learning in Healthcare

Healthcare is facing problems on multiple axes, with low availability of expert care in developing countries and increasing demand for it in the aging population of the first world. Examples are provided showing healthcare applications where machine learning either matches or surpasses human experts. Possible improvements are also explored that AI can bring into the healthcare field while considering the risks and reservations that have prevented it from being the industry standard.

Attendees will learn:

  • How to evaluate the accuracy of a machine learning model against medical expert diagnoses?
  • How might machine learning be eased into healthcare?

Kanty_Milczek_JanJan Kanty Milczek, Senior Data Scientist, deepsense.a

Osterreicher_PawełPawel Osterreicher, Director of Strategy & Business Development,

4:10 PANEL: AI, Deep Learning, and Cybersecurity

Cybersecurity is a major area of interest in today’s internet, and while the threats are no longer as widely discussed as they used to be, they are arguably more dangerous than ever. We show how the constant arms race between security experts and malicious actors is a real-life example of a GAN – a generative adversarial network. We then talk about the ways in which the former may gain advantage. Examples include AI-powered sandboxing and analyses of Big Data unavailable to the attackers. 

Attendees will learn:

  • How machine learning can help with malware research?
  • How image recognition can classify malware?
  • The state of the tech
  • The state of the technology and state of the practice in AI and cybersecurity today

Kanty_Milczek_JanModerator: Jan Kanty Milczek, Senior Data Scientist,



Panelists: Philip Hunter, Research Fellow, Rethink 

Yiqing Wang, PhD, Data Scientist, Microsoft

Seminar Chair Closing Remarks

Robert Bogucki, Chief Technology Officer,

5:00 Close of Seminar

Day 1 | Monday, December 3

Morning Program
Networking Lunch
Concurrent Afternoon Programs
Evening Program
Attendee Breakout Discussions

Day 2 | Tuesday, December 4

Morning Program
Networking Lunch
Concurrent Afternoon Programs
Evening Program
Networking Reception

Day 3 | Wednesday, December 5

Morning Program
Networking Lunch
Concurrent Afternoon Programs