This three-part series of half-day online events gives attendees an overarching perspective of key topics in data and AI today, including deep learning, data analytics, and natural language processing. Each of these areas is pushing the boundaries of what’s possible with more computing power, data, and innovative algorithms.
As you’ll see in this instance, the world of neural networks is constantly changing, with new strategies and techniques for supervised, semisupervised, and unsupervised learning being developed and refined every day. These sessions will explore how using applied neural networks can help inform and improve your computer vision, natural language processing, audio recognition, and other machine learning and AI applications.
About the presenters:
Katy Warr is the author of Strengthening Deep Neural Networks: Making AI Less Susceptible to Adversarial Trickery. She’s the head of AI at Roke Manor Research, one of the UK’s longest established engineering research specialists in AI, cybersecurity, data science, and communications, and has over 20 years' experience developing software for middleware solutions, specializing in policies and security.
Anthony Reina is a medical doctor with extensive experience in AI, neurophysiology, telemedicine, and data science. His biggest claim to fame is spending 12 years as a stay-at-home dad to his two sons while his wife served as a psychiatrist in the US Navy. His current work involves privacy-preserving distributed training for 3D convolutional neural networks in medical imaging (which is much easier than raising two teenage boys).
Chris Van Pelt is a cofounder of Weights & Biases, an experiment tracking platform for deep learning. For the past 10 years, Chris has dedicated his career to optimizing ML workflows and teaching ML practitioners, making machine learning more accessible to all. He founded Figure Eight/CrowdFlower in 2009 and has also worked as a studio artist, computer scientist, and web engineer. He studied both art and computer science at Hope College.
Hanlin Tang is senior director of Intel’s AI Lab—an AI research and engineering group that conducts both foundational and applied ML research, builds several ML open source libraries in reinforcement learning and natural language processing, and delivers algorithms-hardware codesign. He previously led teams in computer vision and federal AI programs at Intel. He joined Intel through its acquisition of the deep learning startup Nervana Systems.
Bargava Subramanian is a cofounder and deep learning engineer at Binaize in Bangalore, India. He has 15 years’ experience delivering business analytics and machine learning solutions to B2B companies. He also mentors organizations in their data science journey. He holds a master’s degree from the University of Maryland, College Park, and is an ardent NBA fan.
Amit Kapoor is a data storyteller at narrativeVIZ, where he uses storytelling and data visualization as tools for improving communication, persuasion, and leadership. Amit leads workshops and training courses for corporations, nonprofits, colleges, and individuals and also teaches storytelling with data as a guest faculty member at IIM Bangalore and IIM Ahmedabad. Amit’s background is in strategy consulting, using data-driven stories to drive change across organizations and businesses. Previously, he spent more than 12 years in management consulting at A.T. Kearney in India, Booz & Company in Europe, and startups in Bangalore. Amit holds a BTech in mechanical engineering from IIT Delhi and a PGDM (MBA) from IIM Ahmedabad.
Table of contents
- Katy Warr: Fooling AI—How Is It Possible, and What Are the Implications?
- Anthony Reina: Doing More with Less—AI Methods for Compressed Sensing in Medical Imaging
- Chris Van Pelt: Building and Debugging Neural Networks (interactive session powered by Katacoda)
- Hanlin Tang: Trends in AI Research—Imitation Learning, Domain Generalization, and Beyond
- Bargava Subramanian and Amit Kapoor: Democratize and Build Better Deep Learning Models with TensorFlow.js
- Title: Strata Data & AI Superstream Series: Deep Learning
- Release date: June 2020
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920455660
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