Dive into the world of visual data processing with our comprehensive CNN course! This program covers everything from the basic principles of Convolutional Neural Networks to advanced applications. You'll begin with an in-depth exploration of CNN architecture, including convolutional layers, pooling layers and fully connected layers, while mastering key concepts like feature extraction, activation functions and loss functions. With practical implementation in MATLAB and Python, you'll learn how to build and optimize CNN models. The primary focus is on explaining the CNN with numerical examples, which gives you hands-on experience in executing the CNN with real numerical data. Through the real example, you'll learn how to transform raw pixel data into feature maps, apply convolution operations and use pooling layers by directly applying the numeric data. You'll also work on optimizing weights and hyperparameters through the numerical examples. Additionally, case studies will explore how CNN works in image classification, along with their performance evaluation. By the end of this course, you'll achieve mastery in CNNs, ready to utilize them across various domains, making it suitable for both beginners and seasoned professionals.
Why CNN is important?
How do CNN works?
CNN Architecture implementation
Xavier/Glorot Initialization
He Initialization
Scaled Random Initialization
Learning rate
Sigmoid
tanh
ReLU
MSE
RMSE
Entropy
MAE
Huber Loss
Gradient descent
Adam
SGDM
Data explanation
Python
Dr.K. Michael Mahesh is an esteemed Associate Professor in the Electronics and Communications Engineering Department at Saveetha Engineering College(Autonomous) in Chennai. His academic voyage commenced with a Bachelor's degreein Electronics and Communication from St. Xavier's Catholic College of Engineering, Nagercoil, affiliated with Anna University Chennai. Subsequently,in 2008, he completed his degree, followed by a Master's degree in Computer and Communication from Sri Sairam Engineering College, Chennai, also under Anna University Chennai's umbrella, in 2011. In 2021, he proudly attained his Ph.D. from Anna University Chennai, a testament to his dedication and scholarly pursuit. With over 12 years of teaching experience, He has honed his expertise in Image Processing, Machine Learning, Deep Learning, and Advanced Driver Assistance Systems(ADAS). His rich research portfolio boasts a multitude of presentations and publications in esteemed international journals and conferences, showcasing his exceptional research prowess and dedication to advancing the field of electronics and communication engineering.
Reviews
Emily Chen
Rahul Sharma
Sophia
Steffan
₹3000
₹8000
$39
$98
This course includes:
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Validity:60 days
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Validity:60 days
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Category:Deep Learning
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Lessons:12
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Students:1908
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Language:English
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Certificates:Yes
Payment details
Convolutional Neural Network
From basics to mastery with numerical examples and case studies.
