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Rock Stars of
Machine Learning and Deep Learning

September 12, 2017 | Mountain View, CA

Machine Learning Deep Learning Badge

Innovation in Machine Learning is Staggering – Can you Keep Up?

 

Amazon, Bank of America, Merrill Lynch, the leaders who are out in front of the latest AI and Machine Learning developments, share their insights at Rock Stars of Machine Learning.

What is most important in AI/Machine Learning today?
Hear in-depth about:

  • Deep learning
  • AI optimized hardware
  • Natural language generation
  • Virtual agents

Get insights into new analytics, algorithms, and data structures that produce reliable, repeatable decisions and results.


How will Machine Learning and Deep Learning control your business?

Hear and interact with C-Suite and upper management executives at Fortune 100 companies and others on Machine Learning and Deep Learning opportunities for 2017.  Also, learn the strategies these industry leaders are utilizing to optimize their business.

 

Venue Address and Date

September 12, 2017

The Computer History Museum

1401 N Shoreline Blvd

Mountain View, CA 94043

 

Why Attend?

Get insights into these critical technologies.

Topics include:

  • Machine Learning

Machine Learning is becoming a key technology that influences C-Suite decisions. Within the field of data analytics, machine learning is a method used to devise complex models and algorithms that lend themselves to prediction. Does your organization employ the proper analytical models that allow your researchers, data scientists, engineers, and analysts to produce reliable, repeatable decisions and results?

  • Deep Learning

What are the promises of deep learning on business?  The science of Deep Learning develops efficient algorithms for unsupervised or semi-supervised feature learning and hierarchical feature extraction from large-scale unlabeled data. Is this the technology solution that your businesses can use to analyze the massive amounts of data becoming available?

 

Key takeaways:

After participating in this event, you will have

  • Actionable technology insights
  • Critical strategies you can apply to your specific business

This is also a great networking opportunity. Attendees will have many opportunities throughout the day to:

  • Interact with C-Level executives in a Q&A and interactive panel format to get answers to specific questions.
  • Interact with speakers and colleagues during expanded break sessions, lunch, and the reception.

 

Speakers

Agenda

Agenda

Morning Session: 9:00 a.m. – 12:30 p.m.

 

Hassan Sawaf

Director of AI
Amazon Web Services

Human Language Technology and Machine Learning

Hassan will discuss his expertise opening up new markets and opportunities with smart application of Artificial Intelligence and application-driven research in AI, in particular in language technology, speech processing, computer vision and computational reasoning.


Janet George

Fellow/Chief Data Scientist, Big Data Platform/Data Science/Cognitive Computing
Western Digital/Sandisk

“Big Metamorphosis”: Spinning up well- Architected Stacks for Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence requires a different treatment of data than the more traditional methods.  The topology and different dimensions of data need to be easily accessible. Distributed platforms and dynamic data structures lend itself well to scale the models near real time. This talk will discuss best practices in spinning up well- architected stacks for machines learning and Artificial Intelligence for scale in an industrial/enterprise setting with practical uses cases, tradeoffs, challenges and storage layers required.

At Western Digital building global core competencies, shaping, driving and implementing the Big Data platform, products and technologies, using advanced analytics, machine learning and pattern recognition with semiconductor/Flash Memory manufacturing data from the ground up. Industry experience, skillset, and background are in Big Data Platform; Machine Learning, Distributed Computing, Compliers and Artificial Intelligence/Cognitive Computing.

 


Parth Vasa

Head of Data Science Engineering
Bloomberg Engineering

Search and Ranking at Bloomberg

Parth Vasa, the Head of Data Science for Bloomberg Engineering, discusses the challenge of providing effective search for financial markets, balancing the need for accuracy and speed, the diversity of the data, and the difficulty of gaining an accurate picture of markets from moment to moment. He will describe the ways in which machine learning is helping Bloomberg to address this challenge.


Veryan Allen

Data Scientist, ML & DL
Bank of America; Merrill Lynch

Program Machines to Deep Learn and Solve Big Data Investment Problems

The discussion will cover all aspects of machine programming with the exploration of Data Science, deep learning, computational intelligence, and multi-criteria decision optimization.


Lunch: 12:30 p.m. - 2:00 p.m.


Afternoon Session: 2:00 p.m. – 5:00 p.m.

 

Joshua Greenbaum (moderator)

Principal, Enterprise Applications Consulting

 

Rajat Monga

Engineering Director
Tensorflow at Google Brain

Trends and Developments in Deep Learning

Deep Learning has come of age over the last few years. Neural networks have been around for decades - what changed over the last few years to make them successful? This talk will describe what got deep learning over the hump, go over some of the recent successes in this field and discuss their implications. The pace of innovation in deep learning is staggering - is it going to continue? The presentation will provide a perspective on research directions that have the potential to keep the innovation going and even accelerate it further.

 

M. Anthony Lewis

Sr. Director
Qualcomm

Understanding How Biologically Inspired Computing May Help us Build Machines that Perceive the World as we do

Lewis will discuss his work in evolutionary and biomorphic robotics, formation control of robotic systems, and investigations into the basis of movement control in humans and robots. Lewis and Colleagues demonstrated a robot that claimed to be the most biologically accurate model of human locomotion to date. This robotic uses a muscle architecture much like a human being, a simplified neural circuit meant to mimic neurons in the spinal cord, and sensory feedback mimicking the primary sensory pathways found in human.

 


 

 Cocktail Reception 5:00 p.m. – 6:30 p.m.

Venue

Venue

The Computer History Museum

 

Rock Stars of Machine Learning/Deep Learning will be held at The Computer History Museum. The Museum is dedicated to preserving and presenting the stories and artifacts of the information age and exploring the computing revolution and its impact on society. The Computer History Museum is a nonprofit organization with a four-decade history and in 2003 opened the Mountain View California building previously occupied by Silicon Graphics.
 
Computer History Museum is located just off US 101; Shoreline Blvd Exit. Parking Computer History Museum offers free onsite parking.
 
Distance from San Jose: 20 miles drive time; 15 minutes 

Attend the Rock Stars of Machine Learning/Deep Learning

The Rock Stars of Machine Learning/Deep Learning will be held on September 12, 2017, at The Computer History Museum.

 

 

 

 

 

 

 

The Computer History Museum

1401 N Shoreline Blvd

Mountain View, CA 94043, USA

Phone: (650) 810-1010

Fax: (650) 810-1055

Directions from San Jose via US-101 North

Take US-101 North toward San Francisco. Take Shoreline Blvd Exit. Turn right onto Shoreline Blvd. Cross through the intersection. The museum is on your right.

Distance from San Jose: 20 miles

Drive time: 15 minutes