Deep Learning | Skillathon

1
Deep Learning An Overview

• Definition, Description and Applications

2
Table of Contents

• Definition
• An Elaborate Description
• Neural Networks
• Applications
• Conclusion

3
A Simplified Definition

• Deep Learning is a concept that uses large
  amounts of labeled data to teach machines to
  react how a human would.

4
An Elaborate Description

• Deep learning techniques use deep neural
  networks.
• Deep neural networks contain as many as 150
  hidden layers.
• The hidden layers enable complex processing of
  large sets of labeled data.

5
Neural Networks

• An Elaborate Description

• The labeled data is fed to the input nodes.
• The hidden layers process the input.
• The result is returned by the output nodes.

6
Applications

• Self Driving Cars
• The system is fed with a million sets of data
  such as data from camera, sensors and geo-mapping
  to enable these cars to make their way through
  traffic.
• Healthcare
• From higher accuracy in diagnosis to discovering
  new drugs to predict the risks of diseases, deep
  learning techniques are revolutionising
  healthcare.

7
Applications

• Visual Recognition
• Visual Recognition which is done using
  convolutional neural networks which is a concept
  of deep learning is useful for sorting out images
  and also for detection of certain objects thus
  enabling classification in images
• Fraud Detection
• Deep learning has enabled the detection of fake
  news by aiding the building of classifiers which
  can pick out the fake news. These classifiers can
  also forbid such news from appearing in your news
  feed.

8
Conclusion
With data multiplying every passing day, deep
learning technologies are extremely vital in the
AI revolution as they help in dealing with
humongous amounts of data. https//skillathon.co/