Machine Learning DevOps - Dockerized
Submitted by Abhinav Shroff (@abhinavshroff) on Thursday, 22 February 2018
Technical level: Beginner Status: Under evaluation
Like the new age internet applications, organizations end up collecting tons of data over the years of usage of enterprise applications. This data can be related to internal users or customers. Data Science and Machine learning can help make this data being usable and available for intelligent decision making. Join us to learn, how Docker along with other Machine Learning tools on cloud can enable you to use the piled up enterprise data to train a machine learning model and start making predictions in a jiffy.
In this session I will cover the basic of an overview of machine learning development process, talk about data preparation phase in ML, challenges in building machine learning system, tools for building machine learning systems and how Docker on cloud can help in establishing a good DevOps process for building ML systems.
No Special Requirements for the session.
Abhinav Shroff works as a Principal Product Manager at Oracle. He is a seasoned professional with wide experience in DevOps, Middleware and Cloud technologies. His areas of expertise are DevOps, Java and ML . He is an active speaker at technical conferences including Java One, Oracle Open World, AIOUG, OTN, Silicon Valley Code Camp, DevOpsDays to name a few and has delivered many technology workshops and sessions.