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IPL Best Batsman and Best Bowler using Principal Component Analysis and Azure

23 november, 2021 | 11:30 fm - 1:00 em (UTC) Koordinerad universell tid

  • Format:
  • alt##LivestreamLivestream

Område: Intelligenta appar (webbutveckling + AI-tjänster)

Språk: Engelska

Cricket Analytics - IPL Best Batsman and IPL Best Bowler using a Dimension Reduction Technique - Principal Component Analysis. We analyze and find the best batsman and best bowler using different metrics such as Most Runs scored, Strike Rate, Wickets Taken, Economy Rate and many more. using We use Principal Component Analysis to reduce the data to 1 and 2 dimensions to rank the batsmen.

We will also build and deploying a Cricket Analytics Streamlit Application in ACI and AKS based on these concepts.

Speaker BIO- Ambarish is a Business and Technology Consultant for more than 20 Years. He is a data lover and compete regularly in data science competitions. He had won Eight Data Science Competition Awards ( 1 sponsored by NASA, Seven sponsored by Kaggle - A Google Company). He presently works with Tata Consultancy Services (TCS) as the Energy Trading and Risk Management Lead, as well as Data Analytics Practice Lead for TCS Utilities. This is a very exciting position where he has the opportunity to combine domain knowledge with data. He is very fortunate to be surrounded by very enthusiastic and energetic people. He do follow cricket, loves to read detective books, and also watch detective films.

Social Handles-
LinkedIn- https://www.linkedin.com/in/ambarish-ganguly/
Twitter- https://twitter.com/a_ganguly/

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