Convolutional Neural Networks
- Offered byUDEMY
Convolutional Neural Networks at UDEMY Overview
Convolutional Neural Networks
at UDEMY
Gain a comprehensive overview of the Neural Networks principles and concepts
Duration | 3 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course |
Credential | Certificate |
Convolutional Neural Networks at UDEMY Highlights
Convolutional Neural Networks
at UDEMY
- Earn a certificate of completion from Great Learning
- Get Free lifetime access
Convolutional Neural Networks at UDEMY Course details
Convolutional Neural Networks
at UDEMY
More about this course
- In this course, we will learn how CNNs work and some of the applications they have been used in
- In this course, we will talk about digital images, the convolution process, and pooling features such as max and average pooling
- We will also uncover kernels and various filters along with feature maps in the Convolution process of CNN
- We will discuss in this course Batch normalization, which is part of Deep Learning
Convolutional Neural Networks at UDEMY Curriculum
Convolutional Neural Networks
at UDEMY
Digital Images Overview
Image as a Function
Edge as a Feature
Digital Noise
Convolution Process
Introduction to Pooling
CNN Theoretical Concepts
Data Augmentation
Weight Initialization
Regularization and Dropout
Demo on CNNs
What is Batch Normalization
Introduction to Convolution Process of CNN
Introduction of Batch Normalization
How does Batch Normalization work?
When and how to use Batch Normalization?
How to evaluate Batch Normalization results?
Regularization and Normalization in Batch Normalization
Why is this Method so important?
What is the side effects of Batch Normalization?
Advantages of using Batch Normalization
Summary of Batch Normalization
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