Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK

Using AWS serverless technologies to analyze large datasets

Krishnan Saidapet (REAN Cloud, A Hitachi Vantara company)
9:0012:30 Tuesday, 30 April 2019
Data Science, Machine Learning & AI
Location: Capital Suite 4
Average rating: ***..
(3.43, 7 ratings)

Who is this presentation for?

  • Those interested in big data and machine learning, AWS, and using serverless cloud data to solve difficult business and analytical problems

Level

Intermediate

Prerequisite knowledge

  • A basic understanding of IT, computer science, and data management

What you'll learn

  • Learn how to use serverless cloud data science and big data tools to solve difficult business and analytical problems

Description

Krishnan Saidapet offers an overview of the latest big data and machine learning serverless technologies from AWS and leads a deep dive into using them to process and analyze two different datasets: the publicly available Bureau of Labor Statistics dataset and the Chest X-Ray Image Data dataset.

For each dataset, Krishnan uses exploratory analytics to introduce the the dataset; shares a hypothesis about the dataset to investigate; explains the high-level architecture of the serverless tools with which to perform the analysis; walks you through preparing and cleaning the data, performing machine learning analysis on it, visualizing the results, and demonstrating key findings and insights from the data; discusses business and real-world use cases; and outlines technical best practices for using serverless tools for big data and machine learning.

You’ll use the Bureau of Labor Statistics dataset to understand patterns and derive insights such as the fastest growing and fastest shrinking jobs in the US and in specific cities, states, and regions of the US as well as wage growth and shrinkage for specific jobs in the US and across cities, states, and regions.

You’ll use the chest x-ray portion to build a CNN model to screen a particular medical condition and build a multiclass classification model to classify chest X-rays into 15 different categories (14 diseases and 1 no disease).

Photo of Krishnan Saidapet

Krishnan Saidapet

REAN Cloud, A Hitachi Vantara company

S.P.T. Krishnan is a computer scientist and engineer with 18+ years of professional research and development experience in cloud computing, big data analytics, machine learning, and computer security. He’s a Google Developer Expert in Google Cloud Platform and an authorized trainer for Google Cloud Platform. He’s also an adjunct faculty in computer science and has taught 500+ university students in the past five years. He has worked as an architect and developer on Amazon Web Services, Google Cloud Platform, OpenStack, and Microsoft Azure. He authored Building Your Next Big Thing with Google Cloud Platform and has spoken at both Black Hat and RSA. He’s also a cofounder of the Google Developer Group, Singapore. Red Hat recently recognized him as the “Red Hat Certified Engineer of the Year.” He holds a PhD in computer engineering from the National University of Singapore, where he studied the performance characteristics of high-performance computing algorithms by evaluating them on different multiprocessor architectures.