Abstract: 

This session focuses on transfer learning and it's uses in various computer vision applications. The attendees would get an overall understanding of the difficulties in training a CNN model from scratch, use of transfer learning techniques and pre-trained models.

Session Outline:

1. Introduction to Deep Learning
2. Introduction to Computer Vision
3. Use of Neural networks in Computer vision(CNN)
4. Overview of steps involved in building a CNN model
5. Introduction to transfer learning
6. Discussion on pre-trained models like VGG -16, YOLO & benefits of using pre-trained models.
7. Use of transfer learning in Computer Vision applications

Background Knowledge:

Basic understanding of Python programming & machine learning

Bio: 

Vaishali is a lead data scientist at Indium Software, a leading digital engineering company. She has 7 years of experience in predictive modeling and data analysis. She designs and develops enterprise-grade solutions based on Machine Learning, Deep Learning, and Natural Language Processing for real-world use cases. As a technology evangelist, Vaishali also coaches aspiring professionals on data science and machine learning at Simplilearn, the world's leading training boot camp. Vaishali holds a professional postgraduate degree in Artificial Intelligence and Machine Learning. She loves cracking Machine Learning Hackathons and has been a winner in many such events.