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Global Artificial Intelligence Virtual Bootcamp – Webinar (Free)

February 11 @ 1:00 pm - 2:00 pm PST

Free
Global Artificial Intelligence Virtual Bootcamp

Webinar Use Kubeflow Pipelines to Deploy Your On-Prem ML Workloads to Google Cloud (by Google) AI, ML & NLP for Enterprise & Government App

About this Event

Webinar Topics :

1. Workshop : Use Kubeflow Pipelines to Deploy Your On-Prem ML Workloads to Google Cloud (Chanchal Chatterjee, Leader In AI Solutions, Google)

2. Workshop : AI, ML & NLP for Enterprise & Government Applications:

— Core Concepts & Algorithms

— Bridging the Last Mile Value Gap

(Prasad Saripalli, VP ML & AI And Distinguished Engineer, MINDBODY)

About this Event

Global Big Data Conference is offering a fast paced, vendor agnostic, technical overview of the AI & Kubernetes landscape. No prior knowledge of AI or programming is assumed. Global Artificial Intelligence Bootcamp is targeted towards both technical and non-technical people who want to understand the emerging world of AI & Devops with a specific focus on Kubernetes, NLP, Deep Learning, Tensorflow, Keras, Machine Learning & comparing frameworks. Attendees will gain hands on experience.

We are very excited to organize 5 day extensive bootcamp on Artificial Intelligence(AI) Feb 22-26 2021. As we get closer to the bootcamp, we want to invite you to participate in Global Artificial Intelligence Virtual Bootcamp Webinar – Online Warm-Up on Feb 11th Thursday (1.00PM – 2.00PM) PST. We will feature with speakers working in AI space.

Free Online Webinar: Feb 11th Thursday (1.00PM – 2.00PM) PST Welcome to webinar hosted by Global Big Data Conference! Please start registering by entering your name and email address to attend Webinar

Webinar info

Feb 11th – 1.00pm – 2.00pm PST

AI, ML & NLP for Enterprise & Government Applications:

— Core Concepts & Algorithms

— Bridging the Last Mile Value Gap

(Prasad Saripalli, VP ML & AI And Distinguished Engineer, MINDBODY)

This Workshop (4 Hours) is a technology, algorithms and application overview in depth (Python) on AI, ML and NLP applications in the Enterprise. It is designed to help enterprise decision makers, data scientists and AI/ML engineers tounderstand the role and use cases of AI, ML and NLP and their applications for tangible RoI. There is broad agreement in the industry and among research communities that AI will significantly add value to the Enterprise economies and global GDP as well.

Profile

Prasad Saripalli serves as the Vice President of ML & AI and Distinguished Engineer at MindBody Inc. – a portfolio company of Vista which manages the world’s fourth-largest enterprise software company after Microsoft, Oracle, and SAP. Earlier, he served as VP Data Science at Edifecs, an industry premier healthcare information technology partnership platform and software provider, where we built Smart Decisions ML & AI Platform with ML Apps Front. Prior to joining Edifecs, he was chief technology officer and VP of engineering at Secrata.com, which provides military-grade cloud security solutions. Previously, he worked as chief technology officer and executive VP at ClipCard and as chief architect for IBM’s SmartCloud enterprise. He also served as GPM on Microsoft’s client virtualization team, which was responsible for shipping Virtual PC on Windows 7, and as a Dev Manager on the Citrix group that built Citrix Presentation Server (now Citrix XenApp). Prasad has doctoral training in Engineering and Computer Science from the University of Florida and post-doctoral training from the University of Texas, and teached ML, Advanced ML, AI, NLP and Distributed Systems at Northeastern University.

Use Kubeflow Pipelines to Deploy Your On-Prem ML Workloads to Google Cloud (Chanchal Chatterjee, Leader In AI Solutions, Google)

Abstract

If you are wondering how to bring your on-prem ML workloads to a scalable, portable, composable and secure production platform, the open source Kubeflow pipelines is your answer. We demonstrate an easy step by step process with ML models from scikit-learn, xgboost and tensorflow ML frameworks. We will show how to create an end to end ML pipeline on the Google Cloud including data prep, hyperparameter tuning, model training, model deployment, prediction, explanation and training orchestration. The solution can be extended to the Anthos framework for a full multi-cloud deployment.

Profile

Chanchal Chatterjee, Ph.D, has several leadership roles focusing on machine learning, deep learning and real-time analytics. He is currently leading Machine Learning and Artificial Intelligence at Google Cloud Platform with a focus on Financial Services and Energy market verticals. Previously, he was also the Chief Architect of EMC CTO Office where he helped design end-to-end deep learning and machine learning solutions for smart buildings and smart manufacturing for leading customers. He was instrumental in Industrial Internet Consortium, where he published an AI framework for large enterprises. Chanchal received several awards including Outstanding paper award from IEEE Neural Network Council for adaptive learning algorithms recommended by MIT professor Marvin Minsky. He has 29 granted or pending patents, and over 30 publications. Chanchal received M.S. and Ph.D. degrees in Electrical and Computer Engineering from Purdue University.

 

Summary
Event
Global Artificial Intelligence Virtual Bootcamp
Location
Online Event,
Starting on
February 11, 2021
Ending on
February 11, 2021
Description
Webinar Use Kubeflow Pipelines to Deploy Your On-Prem ML Workloads to Google Cloud (by Google) AI, ML & NLP for Enterprise & Government App
Offer Price

Organizer

Global Big Data Conference
Phone:
408-400-3769
Email:
events@globalbigdataconference.com
Website:
http://www.globalbigdataconference.com

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