#52 CNN Architecture | Part 2 | VGG Net | Machine Learning for Engineering & Science Applications

Machine Learning for Engineering & Science Applications | IIT Madras - #52 CNN Architecture | Part 2 | VGG Net | Machine Learning for Engineering & Science Applications

Unlock the Future: Master AI & Machine Learning with NPTEL-IITM’s Comprehensive Course! Dive into Neural Networks, Deep Learning, Probabilities, and Optimization Techniques tailored for Engineering & Science Applications. Your AI journey starts here!

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What you'll learn

Understand the historical development and foundational concepts of artificial intelligence.
Gain proficiency in applying machine learning techniques to engineering and science problems.
Develop skills in using linear algebra and calculus for machine learning modeling.
Learn to implement and optimize machine learning algorithms using Python packages.

This course includes

32 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

CNN Architecture Part 2 (VGG Net) Lecture 52

Full Transcript

Welcome to 'Machine Learning for Engineering & Science Applications' course ! Get ready to explore the powerful VGG network architecture, specifically VGG-16, designed for image classification. We'll delve into the concept of blocks of convolutional layers and understand the benefits of using a series of convolutional layers. Discover how this architecture achieves a larger receptive field on the input, enabling the network to capture more context from images. NPTEL Courses permit certifications that can be used for Course Credits in Indian Universities as per the UGC and AICTE notifications. To understand various certification options for this course, please visit https://nptel.ac.in/courses/106106198 #CNNArchitecture #VGGNet #ReceptiveField #ConvolutionalLayers