Machine Learning Design, Demystified

Date/Time
Date(s) - 09/26/18
6:00 pm - 8:00 pm

Location
Google Office

Hosted by
Google Cloud + SoftServe Meet-up


Wed, September 26, 2018 6:00 PM – 8:00 PM

Once available only to scientists, today machine learning (ML) is open to a much broader audience of software architects and engineers. In fact, the practice of ML is so advanced that some algorithm results look like “black magic,” even to experienced practitioners.

 

Join us at the Google Chicago office for our latest meetup, “Machine Learning Design, Demystified” for free food, beer, and discussion on machine learning architecture.

 

Inspired by attribute-driven design (ADD) and Smart Decisions (a software architecture design game for big data), our speakers are excited to share a new version of the game focused on designing ML systems.

 

In this interactive session, you will learn about designing the architecture for ML systems via series of gamified interactive exercises. We will simulate state-of-the-art ML design systems by analyzing both business and technical requirements, selecting the best matching algorithms, and teaching how to validate early design decisions using rapid prototyping techniques.

 

Attendees are encouraged to think of an ML use case and bring it for discussion.

 

Don’t forget to register to secure your spot!

REGISTER HERE

About the Speakers:

 

 

 

 

Serge Haziev – VP Technology Services Group
Serge has more than 18 years’ experience in designing, evaluating and modernizing large scale software architectures in various technology domains including BI, Big Data, Clouds, SOA and Carrier-grade telecommunication services for both Fortune 100 and startups.

 

 

 

Iurii Milovanov – Data Science Practice Leader
Iurii has more than 8 years’ experience in enterprise-level solutions including Big Data, data mining, and information security. He specializes in scientific and algorithmic approaches to solving various business tasks using state-of-the-art AI techniques, such as deep learning, computer vision, natural language processing, and speech recognition.

 


 

Agenda:

 

6:00 PM – Doors Open

6:15 PM – Speaker + Q&A

7:15 PM – Networking

Category(ies)


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