Deep Learning :The Complete Guide with CNN and ANN

The advance guide to master deep learning and build models using CNN and ANN

Within the AI ecosystem, Deep Neural Network or CNN are the most popular sub-fields that promise to change multiple businesses globally. 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.

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.

Course Content

  • Introduction –> 6 lectures • 40min.
  • Neural Networks –> 6 lectures • 49min.
  • Artificial Neural Networks –> 14 lectures • 3hr 7min.
  • Convolutional Neural Networks –> 5 lectures • 1hr 43min.

Deep Learning :The Complete Guide with CNN and ANN

Requirements

  • Basic knowledge of Python is important to complete this course.
  • This course assumes knowledge of foundational mathematics.

Within the AI ecosystem, Deep Neural Network or CNN are the most popular sub-fields that promise to change multiple businesses globally. 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

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