Practical Deep Learning
Submitted by Arthi Venkataraman (@arthi) on Friday, 15 April 2016
Technical level: Intermediate
This session will equip users with knowledge on Deep Learning. At end of session audience should have sufficient knowledge of deep learning networks, where they can be applied and what are the benefits of using the same. They will also get some practical tips on implementing these algorithms. An overview of how we build a a Text classifier using deep learning approach will be given. Results obtained on same will be show cased. Our lessons learnt while working with deep learning networks will be discussed.
This session will cover What is Deep Learning, What can you do with deep Learning, What is it’s relationship with Machine Learning, Brief introduction to the working of an Artificial neural network, Introduction to a Deep Learning Algorithm (Long Short Term Memory Networks ), Availabe frameworks for deep learning, An overview of how we built a working text classification system using LSTM in python, Tips based on experience with deep learning networks
Basic understanding of machine learning concepts can help to better appreciate the presentation though this is not mandatory.
Arthi Venkataraman has 19+ years of experience in the design, development and testing of projects in different domains • She is currently a Senior Member in the Distinguished Members of Technical Staff cadre at Wipro Technologies • Her current role involves solution development for different business problems spanning the area of Natural Language Processing, Machine Learning and Semantics Technologies
She has a B.E Degree in Computer Science from University Visvesvariah College of Engineering, Bangalore and an MBA (PGDSM) from IIM, Bangalore. She has previously presented papers and spoken at other international conferences This presentation is based on Arthi’s experience in area of building a large scale production grade classifier using Python at her organization.