Use of Transfer Learning in Computer Vision


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


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.

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