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Jim Baker

Jim Baker

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Introduction

AI has potential in creating value in terms of enhanced workload availability and improved performance and efficiency for NFV usecases. This work aims to build Machine-Learning models that can be used by Telcos. Each of these models aims to solve single problem within a single category. For example, the first category we have chosen is Failure prediction, and we aim to create 4 models - failure prediction of VMs, Containers/Pods, Nodes, and Applications.

Advisors

  1. Sridhar K. N. Rao (Sridhar Rao)

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Weekly Meeting minutes

04-June-2021Thoth-2021-07-09.mp4



Volunteer Contributions


Sl. No.ContributorContributionDurationCertificate of Appreciation OR Contribution
1Girish L

Survey of:

  1. Existing works on AI/ML in Networking - works related to NFV - problems, ML-Techniques, Data, etc.
  2. NFV Problems - Event Correlation, VNF Placement, Anomaly Detection, VNF Failure Prediction, and Synthetic Data Generation.
  3. OSS Projects for AI/ML that can be (re)used
1 Month

ML-Networking-Telcos Survey  











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