When you enroll through our links, we may earn a small commission—at no extra cost to you. This helps keep our platform free and inspires us to add more value.

Udemy logo

Convolutional Neural Network

Learn the fundamental aspects to design a convolutional neural network architectures by given steps of modeling

     
  • 2.9
  •  |
  • Reviews ( 2 )
₹519

This Course Includes

  • iconudemy
  • icon2.9 (2 reviews )
  • icon56m
  • iconenglish
  • iconOnline - Self Paced
  • iconprofessional certificate
  • iconUdemy

About Convolutional Neural Network

Artificial intelligence is a large field that includes many techniques to make machines think, which means endowing this machine with intelligence, unlike, as we all know, the habitual intelligence exhibited by humans and animals. Therefore, in this course, we investigate the mimicking of human intelligence on machines by introducing a modern algorithm of artificial intelligence named the convolutional neural network, which is a technique of deep learning for computers to make the machine learn and become an expert. In this course, we present an overview of deep learning in which, we introduce the notion and classification of convolutional neural networks. We also give the definition and the advantages of CNNs. In this course, we provide the tricks to elaborate your own architecture of CNN and the hardware and software to design a CNN model. In the end, we present the limitations and future challenges of CNN. The essential points tackled in this course are illustrated as follows: - What is deep learning? - Why are computational intelligence algorithms used? - Biomimetics inspiration of CNN from the brain - Classification of deep learning (CNN) - The kinds of deep learning algorithms - Definition of convolutional neural networks - Advantages of Convolutional Neural Network - The pupose of CNN - Architecture of CNN - Training and optimization of CNN parameters - Hardware material used for CNN - Software used for deep learning - Famous CNN architecture - Application of CNN - Limitation of CNN - Future and challenges of convolutional neural networks - Conclusions

What You Will Learn?

  • The overview of the deep learning field .
  • Steps to design a Convolutional Neural Network models .
  • Limitation, future, and challenges of Convolutional Neural Networks .
  • The Convolutional Neural Networks models .
  • The Hardware involved for CNN .
  • Software used for CNN .
  • The application of CNN.