Introduction to Convolutional Neural Networks: : With Image Classification Using PyTorch / Milosevic, Nemanja.

Format:

Video

Author/Creator:

Milosevic, Nemanja, author.

Language:

English

Subjects (All):

Neural networks (Computer science).

Image processing--Digital techniques.

Image processing.

Machine learning.

Artificial intelligence.

Genre:

Electronic videos.

Physical Description:

1 online resource (1 video file, approximately 1 hr., 21 min.)

Edition:

1st edition

Place of Publication:

Apress, 2020.

System Details:

video file

Summary:

In this video course, you will learn the basic principles of neural networks that are used to build models. You'll start by seeing machine learning, neurons, activations, activation functions, weights, and how everything works under the hood. Next, you'll cover the basics of the learning loop including how backpropagation and gradient descent work. Further, you will learn about convolutions, how they are inspired by the animal visual cortex, and how we use them in neural networks. One of the focuses of the course is image classification and detecting common objects in images. This has many uses in your day-to-day projects. We will be using the PyTorch open-source neural network library here. The course will also cover current state-of-the-art neural network models and show how to use them even on smaller hardware. The video concludes by showing some common tricks with hyperparameter settings and regularization techniques, and how to use neural networks in production environments. What You Will Learn Discover the basics of neural networks and how they function Work with convolutional neural networks Use CNNs in your day-to-day work for image classification and other tasks Who This Video Is For Data scientists and machine learning and deep learning engineers.

Participant:

Presenter, Nemanja Milosevic.

Notes:

Online resource; Title from title screen (viewed January 29, 2020)

Title from resource description page (Safari, viewed June 25, 2020).

OCLC:

1160207378