Design Thinking Principles for Machine Learning Problems | Edtech Events

Design Thinking Principles for Machine Learning Problems

Phoenix, Arizona Aug 21 6:30 pm

Price: Free


With so much of hype around ML/AI and many companies claiming they offer AI products, how do we identify the right use cases and problems that really fit Machine Learning realm that can help Customers enable an Intelligent Enterprise? How can you better collaborate with Customers to identifying the right problems that ML can solve for their business?

In this session, we will introduce Design Thinking methods, its’ areas of application in Machine Learning projects, as well as important tools and techniques. We will provide a comprehensive understanding of Design Thinking as a process and mindset needed for an innovative organizational culture undertaking Machine Learning or any innovation projects.

We will further look at a Machine Learning case study of Fuel Consumption Optimization through Prescriptive Analytics, Aviage Systems: Aviage is a joint venture between General Electric Company and Aviation Industry Corp. of China for whom a data-driven online recommendation system for fuel conservation was built. This was implemented using hardware-based machine learning algorithms to accurately calculate real-time fuel flow rates & linear/non-linear programming to prescribe True airspeed to minimize Fuel Flow rate.

Schedule:

6:30-6:45: Food & Networking6:45-7:00: Announcements & Speaker Intros7:00-8:00: Presentation8:00-8:15: Questions8:15-8:30: Wrap-up and "High-Five Everyone Til Next Time"

Speakers:

Raghav Jandhyala is a Senior Director of Product Management at SAP Labs for IOT and Digital Supply Chain. Author of three books on Digital Supply Chain, Raghav has over 16 years of experience in different fields like Supply Chain Management, Retail and Banking along with a strong technical background in Big Data, Cloud, Machine Learning, Business Intelligence and drives development and adoption of business applications. He has Masters in Computer Science from Southern Illinois University along with Cloud Computing and Predictive insights from Stanford University and Advanced Machine learning and Artificial Intelligence, Harvard University. He held various roles in his career as Business Consultant, Development Architect, Solutions and Product Management. Raghav works with Strategic Customers for new product innovations and as a trusted advisor for their Business Transformations. His interest is to bridge Business and Technology and is also a Guest Speaker at ASU WP Carrey School of Business.

Aishwarya(Ash) Sharma is Business Analytics 2018 grad from ASU with experience in Data Science technology on legacy systems. She built machine learning models for aircrafts, revenue management and market research.

About Galvanize:

Galvanize is the premiere dynamic learning community for technology. With campuses located in booming technology sectors throughout the country, Galvanize provides a community for each the following:

  • Education - part-time and full-time training in web development, data science, and data engineering
  • Workspace - whether you’re a freelancer, startup, or established business, we provide beautiful spaces with a community dedicated to support your company’s growth
  • Networking - events in the tech industry happen constantly in our campuses, ranging from popular Meetups to multi-day international conferences

To learn more about Galvanize, visit galvanize.com.

Galvanize
515 East Grant Street
Phoenix, Arizona

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