What you'll learn

Learn the core concepts of Deep Learning

Learn to use tools to build CNN models

Learn practical ANN and its application on real world use cases

Requirements

Basic knowledge of Python is important to complete this course

This course assumes knowledge of foundational mathematics

Description

Moreover, a tremendous interest in CNN has emerged in recent years. It is mostly because of its property of 'spatial in variance' that is useful for computer vision and other similar tasks. Probably this is why CNN has managed to become one of the hottest topics of artificial intelligence.

To give you a complete understanding of this concept, we have curated this exclusive online tutorial that will help you learn all the aspects of Deep Neural Network or CNN and Artificial neural nets (ANN)

What You'll Learn?

This course unfolds with the basic intro of Deep Learning and then directly jumps into CoLab & other essential tools of Neural Networks & Artificial Neural Network. As it progresses, it will give you detailed insights into architectures of CNN, convolutional layers, fully connected layers, and training a deep neural network. In the end, it is also supported by a project that entirely revolves around Deep Neural Network & CNN.

This Course Includes:

l Intro- Deep Learning, CoLab,

l Neural Networks- Working, APIs, Architecture, Training & Testing

l Artificial Neural Networks- Working, Learning, Gradient Descent, Backpropagation, SGD, Optimization

l CNN- Architectures, Convolutional Layers, Pooling, Fully Connected Layers, Activation Functions, Training Deep Neural Networks

l Project on Deep Neural Network & CNN

B with this course to learn CNN & harness the true power of Deep Learning!

Who this course is for:

Anyone who wants to learn Deep learning and CNN will find this course very useful



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