All in One Offer! | Access Unlimited Courses in any category starting at just $29. Offer Ends in:

Browse Library

  • Business Solutions
  • Become an Instructor
  • 0
    Shopping Cart

    Your Cart is empty. Keep shopping to find a course!

    Browse Courses

Deep Learning

Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers.

Students Learning : 60954
Filter
Language
Ratings
Views
Level
Done
Explore Deep Learning Courses
Our Learners works at
You may be also interested in

Learn more topics in various categories at one place. Explore unlimited courses in other categories and up-skill yourself today.

Web Development Programming Languages Game Development Databases Software Testing Software Engineering Development Tools E-Commerce Cloud Computing Data Science Mobile Apps
More Courses in Deep Learning
Frequently asked questions
  • What is Deep Learning?

    Deep Learning is a subset of machine learning that involves neural networks with multiple layers (deep neural networks). It excels in learning complex patterns and representations from data.

  • How does Deep Learning differ from traditional machine learning?

    Deep Learning employs neural networks with deep architectures, allowing it to automatically learn hierarchical features and representations, eliminating the need for manual feature engineering.

  • What are Neural Networks in Deep Learning?

    Neural Networks are the fundamental building blocks of Deep Learning. They consist of interconnected layers of nodes (neurons), each layer learning different features and contributing to the model's overall capability.

  • What are common applications of Deep Learning?

    Deep Learning is applied in various domains, including image and speech recognition, natural language processing, autonomous vehicles, healthcare diagnostics, and recommendation systems.

  • What is the role of Training and Backpropagation in Deep Learning?

    Training involves feeding data into a neural network, adjusting weights based on predictions, and optimizing the model. Backpropagation is the process of iteratively updating weights by minimizing the difference between predicted and actual outcomes, enhancing model accuracy.

Students learning on Learnfly works with Fortune 500 companies around the globe.

Sign Up & Start Learning
By signing up, you agree to our Terms of Use and Privacy Policy
Reset Password
Enter your email address and we'll send you a link to reset your password.