In this session, you will learn about the high-level API Keras and how to implement a neural network using Keras. You will also explore some best practices for training neural networks.
In this Session
We will cover the following topics:
- Keras: High-level API using TensorFlow
- Implementation of neural networks using Keras
- Epoch, batch, overfitting and underfitting
Prerequisites
As the main prerequisites for this session, you must have a good understanding of the topics covered in the previous sessions of this module.
Guidelines for In-Module Questions
The in-video and in-content questions for this module are not graded.
People you will hear from in this session
Subject Matter Expert:
Professor, IIIT-Bangalore
G. Srinivasaraghavan, PhD is a Partner at Performance Engineering Associates. He has a PhD in Computer Science from the Indian Institute of Technology Kanpur and has over 18 years of industry experience. At Infosys Technologies, India’s premier IT firm, he was responsible for the delivery of large, performance-critical IT systems for Fortune 500 clients in the telecom, BFSI and logistics spaces. He has over a dozen published papers in several reputed international fora, including journal of Algorithms, International Journal on Computational Geometry and Applications and Foundations of Software Technolgy and Theoretical Computer Science. In his previous position he was Chief Technology Officer at Aztecsoft Ltd(now a part of Mindtree Ltd), where he brought about a radical, product-quality-focussed shift in the firm’s approach to quality assessment.
Gunnvant is experienced analytics professional with a demonstrated history of working in EdTech. He has designed and helped launch machine learning, data science, and deep learning training programs for learners with varied skillsets and different career expectations. He has also been involved in tech advocacy.
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