Description

 MLOps holds the key to accelerating the development, deployment and management of AI, so that enterprises can derive real business value from their AI initiatives.  Deploying and managing deep learning models in production carries its own set of complexities.  In this talk, we will discuss real-life examples from customers that have built MLOps pipelines for deep learning use cases.  For example, predicting rainfall from CCTV footage to prevent flooding.  We’ll finish off with a live mask detection demo, showing how to detect individuals who are or aren’t wearing masks in public areas at scale, to help prevent the spread of COVID-19.  Throughout these examples, we will share best practices to effectively build, deploy and manage deep learning pipelines in production.  We’ll show how to automate, accelerate and scale the data science practice effectively, how to enable continuous development and delivery (CI/CD) of data and ML intensive applications, how to integrate many types of data (images, video etc.) from different sources, and how to set up the foundation to account for an evolving set of use cases of growing complexity.


Instructor's Bio

Yaron Haviv

Co-Founder and CTO, Iguazio

Yaron Haviv is a serial entrepreneur who has been applying his deep technological experience in data, cloud, AI and networking to leading startups and enterprise companies since the late 1990s. As the co-founder and CTO of Iguazio, Yaron drives the strategy for the company’s data science platform and leads the shift towards real-time AI. He also initiated and built Nuclio, a leading open source serverless platform with over 3,400 Github stars and MLRun, Iguazio’s open source MLOps orchestration framework. 

Prior to co-founding Iguazio in 2014, Yaron was the Vice President of Datacenter Solutions at Mellanox (now NVIDIA), where he led technology innovation, software development and solution integrations. He was also the CTO and Vice President of R&D at Voltaire, a high-performance computing, IO and networking company which floated on the NYSE in 2007. Yaron is an active contributor to the CNCF  Working Group and was one of the foundation’s first members. He presents at major industry events and writes tech content for leading publications including TheNewStack, Hackernoon, DZone, Towards Data Science and more.

Github | LinkedIn | Twitter

Guy Lecker

ML Engineer, Iguazio

Guy Lecker is a Machine Learning Engineer at Iguazio. He is part of the CTO office which develops Iguazio’s enterprise MLOps platform and open source MLOps Orchestration Framework - MLRun, and advises its enterprise data science customers and users.

Guy has a BSC in Computer Science from the Technion - Israel Institute of Technology, with a focus on machine and deep learning.

Before working at Iguazio, Guy worked as a Deep Learning Engineer at Mobileye, optimizing deep learning models for the autonomous vehicle and developing Mobileye’s quantization and testing tools.

LinkedIn


Webinar

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    ON-DEMAND WEBINAR: Automating MLOps for Deep Learning

    • Ai+ Training

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