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About This Course

Get a crash course on the what there is to learn and how to go about learning more. Deep Learning presents a simplified explanation of some of the hottest topics in data science today:
  • What is Deep Learning?
  • What are are convolutional neural networks?
  • Why is deep learning so powerful and what can it be used for?
  • Be part of a rapidly growing field in data science; there's no better time than now to get started with neural networks.

Course Syllabus

  • Module 1 - Deep Learning Concepts
    1. What is a neural network?
    2. Why Deep Learning?
    3. How to choose between deep neural networks?
    4. An old problem: The Vanishing Gradient
    5. Restricted Boltzmann Machines
    6. Deep Belief Networks
  • Module 2 - Deep Learning Concepts Continued
    1. Convolutional Networks
    2. Recurrent Nets
    3. Autoencoders
    4. Recursive Neural Tensor Nets
    5. Deep Learning Use Cases
  • Module 3 - Platforms for Deep Learning
    1. What is a Deep Learning Platform?
    3. Dato GraphLab
  • Module 4 - Deep Learning Software Libraries
    • What is a Deep Learning Library?
    • Theano
    • Deeplearning4j
    • Torch
    • Caffe

General Information

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be audited as many times as you wish.

Recommended skills prior to taking this course

  • None


  • None

Course Creator Info

Introduction to Deep Learning


DeepLearning.TV is all about Deep Learning, the field of study that teaches machines to perceive the world. Starting with a series that simplifies Deep Learning, DeepLearning.TV features topics such as How To’s, reviews of software libraries and applications, and interviews with key individuals in the field. Through a series of concept videos showcasing the intuition behind every Deep Learning method, we will show you that Deep Learning is actually simpler than you think. Our goal is to improve your understanding of the topic so that you can better utilize Deep Learning in your own projects. We hope to provide a window into the cutting edge of Deep Learning and bring you up to speed on what’s currently happening in the field.
  1. Course Number

  2. Classes Start

    Any Time, Self-Paced
  3. Estimated Effort

    3 hours