ConvNets: Introduction to Convolutional Neural Networks


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Explore convolutional neural networks, their different types, and prominent use cases for machine learning, in this 10-video course. Learners will study the different layers and parameters of convolutional neural networks and their roles in implementing and addressing image recognition and classification problems. Key concepts covered in this course include the working mechanisms of convolutional neural networks, and the different types of convolutional neural networks that we can implement; and problems associated with computer vision, along with the prominent techniques to manage them.  Next, you will learn about the role of neural networks and convolutional neural networks in implementing and addressing image recognition and classification problems; observe the prominent layers and parameters of convolutional neural networks for image classification; and learn to see the convolutional layer from a mathematical perspective, while recognizing the mathematical elements that enter into the convolution operations. Finally, learners will be shown how to build a convolutional neural network for image classification by using Python.



Expected Duration (hours)
1.0

Lesson Objectives

ConvNets: Introduction to Convolutional Neural Networks

  • discover the key concepts covered in this course
  • define the concept of convolution neural networks and recognize the prominent uses cases of convolutional neural networks
  • describe the working mechanism of¬†convolutional neural networks
  • recognize the different types of convolutional neural networks that we can implement
  • describe the problems associated with computer vision along with the prominent techniques to manage them
  • identify the role of neural networks and convolutional neural networks in implementing and addressing image recognition and classification problems
  • recognize the prominent layers and parameters of convolutional neural networks for image classification
  • describe convolutional layer from mathematical perspective and recognize the mathematical elements that enter into the convolution operations
  • build a convolutional neural network for image classification using Python
  • recall the prominent use cases of convolutional neural networks, list the different types of convolutional neural networks, and build a simple convolutional neural network for image classification
  • Course Number:
    it_mlfscndj_01_enus

    Expertise Level
    Beginner