Global Data Science Forum

Deep Learning Fundamentals 

6 days ago

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 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.


Please note that version 2.0 of this course was released on August 23, 2017. Please refer to the section in the course for a detailed description of the changes and updates.

COURSE SYLLABUS

  • Module 1 - Introduction to Deep Learning
    1. Why Deep Learning?
    2. What is a neural network?
    3. Three reasons to go Deep
    4. Your choice of Deep Net
    5. An old problem: The Vanishing Gradient
  • Module 2 - Deep Learning Models
    1. Restricted Boltzmann Machines
    2. Deep Belief Nets
    3. Convolutional Networks
    4. Recurrent Nets
  • Module 3 - Additional Deep Learning Models
    1. Autoencoders
    2. Recursive Neural Tensor Nets
    3. Deep Learning Use Cases
  • Module 4 - Deep Learning Platforms and Software Libraries
    1. What is a Deep Learning Platform?
    2. H2O.ai
    3. Dato GraphLab
    4. What is a Deep Learning Library?
    5. Theano
    6. Caffe
    7. TensorFlow

 

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

 

REQUIREMENTS

  • None

Statistics
0 Favorited
6 Views
0 Files
0 Shares
0 Downloads

Tags and Keywords

Related Entries and Links

No Related Resource entered.