Doing Data Science on Cloud
Submitted by Swapnil Dubey (@swapnildubey) on Monday, 13 November 2017
With the increase in data size for running DS models,it is important to look into possible infrastructure options which provide enough scalability to run DS algo successfully.Optimal use of infrastructure in terms of cost is the need of hour.For example,running task using multiple GPU for finite amount of time. Almost all the Cloud vendors(AWS,Google,Microsoft) provide different kind of services for this situation.This talk will primarily make a comparison into advantages and disadvantes of such services provided by cloud providers.It will also look into various options for running tasks in a particular cloud provider.
The presentation is purely on the basis of study which we did in the past.
Data scince on Cloud:
Importance of running DS on Cloud?
Options for running ML on cloud platform
- Using native compute and storage only. - Hosted Data platfrom - Machine Learning Services - Congnitive API Services. Demo : Using Cognitive Services of Google Cloud Platform- GCP vision API.
Options for running scalable DS models on Cloud:(Advantage, Disadvantage, Pricing)
- AWS - Azure Machine learning - Google Cloud ML Other providers: IBM bluemix vs Sense.io vs Domino datalab vs Datajoy
Demo: Running DS models using Tensorflow on Google Cloud ML(Using GPUs).
- Swapnil is right now contributing to Schlumberger Data Science team applying analytics in field of Oil and Natural Gas.Prior to this he was part of Snapdeal Realtime Analytics team as Lead Enginner.
Swapnil in the past has worked as Cloudera Trainer.He belives in learning and sharing his learning across the community.A frequent speaker in meetups and active presenter in conferences.
With more than 8+ years of experience, Swapnil has contributed in Domains of BFSI,Ad Serving and eCommerce with Hadoop,Spark and GCP as primary tech stack.
Past conferences & Meetups:
Dr Dobbs conference-Bangalore- April 11-12,2014
Ekansh Verma is right now working with Schlumberger Data Scince team as Data scientist.He has done his Bachelors, Biomedical Engineering from IIT Chennai.He has good understanding of Deep Learning concepts. His primary expertise lies in Image classfication.