Jyotsna Khemka
Sr. Technical Consulting Engineer
Intel
location_on India
Member since 5 years
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Jyotsna Khemka
Specialises In (based on submitted proposals)
Jyotsna is a Technical Consulting Engineer at Intel. She has got more than 13 years of work experience in software application development, applied research in parallel systems, parallel programming using multicore (OpenMP, MPI), many-core, use of accelerators in various domains including medical image processing, computational chemistry, and computational fluid dynamics. She has a passion for optimizing & scaling real-world applications on large-scale parallel & distributed systems. In her current role, she is supporting customers in optimizing their applications on distributed platforms using Intel Cluster Tools. She is also actively involved in trainings in parallel computing and Intel Software Tools. She holds a Master’s degree in Computational Engineering from FAU, Germany.
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Distributed Deep Learning on Spark CPU Clusters with Intel BigDL
Jyotsna KhemkaSr. Technical Consulting EngineerIntel
Dr. Amarpal S KapoorSoftware Technical Consulting EngineerIntelschedule 5 years ago
480 Mins
Workshop
Beginner
Are you or your customers running on Apache Hadoop and Spark clusters? Are you curious on how you can run Deep Learning for inference and training datasets on your existing Hadoop or Spark CPU clusters without having to migrate your data from one setup to another – experience how easy it is to run DL on your general purpose CPU. This workshop will help you - Get Started on your journey with Intel's Big Data Deep learning Library - BigDL.
Join AI experts at Intel for a deep-dive workshop to learn about computer vision and deep learning.
- Technical overview of BigDL architecture and learn:
- How it fits in the Apache Spark stack
- Key features
- Resources, code samples, and tips
- Build with BigDL
- Learn how to deploy BigDL on-premise or in the cloud to build end-to-end solutions.
- Review case studies
- Experience real-life demos
- Technical overview of BigDL architecture and learn:
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