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Register for one or more webinars below. If you missed a webinar, not to worry! Click here for the AI on-demand webinars. Remember we will be adding new AI webinars regularly, so bookmark this page!

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May 1
9:00 AM PDT

Deep-dive and Use-cases with the Intel® Distribution of OpenVINO™ toolkit


The Intel® Distribution of OpenVINO™ toolkit enables enterprise and academic developers alike to develop performance applications with relative ease.

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A previous webinar introduced the inference engine to the community of developers as the component to use to develop realtime applications. This webinar will perform a deep-dive on the capabilities of the inference engine and the API that enables creation and deployment of said applications. During this webinar a selection of use-cases will be reviewed in the context of the model/topologies used and the various hardware targets they employed.
You will learn:

  • A review of the OpenVINO toolkit
  • A deep-dive of the inference engine API via a code walkthrough
  • A survey of use-cases and applications developed for various hardware targets

Rudy Cazabon, AI Developer Evangelist at Intel

Bachelor’s degree in Space Science (minor in Mechanical Engineering) from the Florida Institute of Technology; with graduate studies in Aerospace and Astronautics from Georgia Tech and Management Science from Stanford. Rudy has run a technical consultancy in 3D graphics, VR, and computer vision; and is an active volunteer in STEM K-12 programs and participates in academic venues such as ACM Siggraph.


May 16
9:00 AM PDT

Introduction to the 2nd Gen Intel® Xeon® Scalable Processor


This webinar will provide an overview of key deep learning workloads and trends mapped to industry use cases.

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We will introduce the new 2nd Gen Intel® Xeon® Scalable processor with Intel® Deep learning boost and its benefits for Deep learning inference applications. We will demonstrate performance improvements with both the new embedded AI acceleration and software optimizations. We will also share examples of real world deployments including pointers to deploy Deep learning on Xeon.

Banu Nagasundaram

Banu Nagasundaram is a product marketing manager with the Artificial Intelligence Products Group at Intel, where she drives overall Intel AI products positioning and AI benchmarking strategy and acts as the technical marketer for AI products including Intel Xeon and Intel Nervana Neural Network Processors. Previously, Banu was a product marketing engineer with the Data Center Group at Intel, where she supported performance marketing for Xeon Phi, Intel FPGA, and Xeon for AI; was a design engineer on the exascale supercomputing research team with Intel Federal; and worked at Qualcomm doing design verification of mobile processors. Banu holds an MS in electrical and computer engineering from the University of Florida and is working toward an MBA at UC Berkeley’s Haas School of Business.

Indu Kalyanaraman is a AI Performance Marketing Manager for Data Center products at Intel. She is responsible for driving performance analysis and product positioning for Machine Learning and Deep Learning workloads on Xeon and other data center products. In her previous roles at Intel, Indu worked on Workstation and Storage/Ethernet performance marketing; Indu also has broad engineering experience including managing a processor validation team. Indu holds an MS in Electrical and Computer Engineering from The Ohio State University


Webinars Now On-Demand

Did you miss a live webinar? Not to worry. All of the webinars have been recorded and are available to watch at your convenience. Check the box(es) to the webinar(s) you would like to view, enter your info to sign up if you have not registered already, and you will be mailed a link to view.

Introduction to Reinforcement Learning Coach

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Reinforcement Learning Coach (RL Coach) is a comprehensive framework that enables reinforcement learning (RL) agent development, training, and evaluation.

Join us for a webinar introducing Reinforcement Learning Coach. RL Coach is a comprehensive framework that enables reinforcement learning (RL) agent development, training, and evaluation. Learn the basics of what Reinforcement Learning is, what exactly is RL Coach, and how you can get started with using RL Coach.

Michael Zephyr is an AI Developer Evangelist within the Intel Architecture, Graphics and Software Group at Intel. He works on promoting various Intel technologies that pertain to machine learning and artificial intelligence and regularly speaks at universities and conferences to help spread knowledge of AI. Michael holds a bachelor's degree in Computer Science from Oregon State University and a master's degree in Computer Science from the Georgia Institute of Technology. He can often be found playing board games or video games and lounging with his wife and cat in his free time.

Introduction to the Intel® Distribution of OpenVINO™ Toolkit and WinML*

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In this webinar you will learn how real-time inference on the PC for visual workloads such as object detection, recognition, and tracking are now easily developed with Intel® Distribution of the OpenVINO™ toolkit and Windows Machine Learning API.

Rudy Cazabon - Bachelor’s degree in Space Science (minor in Mechanical Engineering) from the Florida Institute of Technology; with graduate studies in Aerospace and Astronautics from Georgia Tech and Management Science from Stanford. Rudy has run a technical consultancy in 3D graphics, VR, and computer vision; and is an active volunteer in STEM K-12 programs and participates in academic venues such as ACM Siggraph

Introduction to NLP Architect

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This webinar focuses on introducing the audience to Natural Language Processing (NLP) Architect, a Python library from the Intel® AI Lab for exploring the state-of-the-art deep learning topologies.

You will learn:

  • Intel’s AI Portfolio
  • What is Natural Language Processing
  • What is Deep Learning
  • Deep Learning Techniques with Natural Language Processing
  • How can NLP Architect be used
  • NLP Architect Library Overview

Abdulmecit Gungor has received Bachelor of Electronics Engineering and a minor degree in Mathematics from City University of Hong Kong with The S. H. Ho Foundation Academic achievement reward. He has worked as a research engineer, then completed his Master degree at Purdue. His interests are NLP application development on real life problems, text mining, statistical machine learning.

Sulaimon Ibrahim is a member of the Intel’s Technical Developer Evangelist team, focused on highlighting, training and showcasing Intel products and tools to developers worldwide. He currently focuses on Artificial Intelligence, developing coursework for Intel’s developer ecosystem and then delivering trainings for both industry and academic developers interested in using Intel’s optimized frameworks and libraries. Sulaimon has been in the tech industry for over 7 years and has a master’s Degree in Computer Science with researches in Data Mining.

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