Beginner's Guide to Deep Learning

divyam3897


10

Votes

Description:

What is deep learning?

It has recently exploded in popularity as a complex and incredibly powerful tool. This talk will present the basic concepts underlying deep learning for complete beginners. We will review the basic fundamentals of it and code up a simple neural network in Keras. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow which allows easy and fast prototyping of a problem. The talk will be structured as below:

  1. What is deep learning?
  2. Why should I care and learn it?
  3. What is a neural network?
  4. A simple example
  5. Predictions with our neural network and results.

Prerequisites:

  • Python programming fundamentals.
  • Basic knowledge of keras and tensor flow (completely optional as will be covered in the talk).

Content URLs:

The slides will be added soon on Github..

Speaker Info:

Divyam Madaan is an open source enthusiast contributing as a core developer at GCompris which is a high quality educational software suite comprising of numerous activities for children aged 2 to 10. He has been a Season of KDE developer and also a Google summer of Code student, 2017.

He is a Pythonista who works on projects which make life easy for people using AI and the web. He has been working as a Software Developer at KDE from more than one year. He has taken various workshops and talks in his college for students. He has also been a speaker at KDE India Conference and his talks were also selected at Akademy happening in Almeria, Spain and FOSSCON, US.

Speaker Links:

Github: https://github.com/divyam3897

KDE Phabricator: https://phabricator.kde.org/p/dmadaan/

linkedin: https://www.linkedin.com/in/divyam-madaan-0bb627105/

Twitter: https://twitter.com/divyam3897

Section: Data Analysis and Visualization
Type: Talks
Target Audience: Beginner
Last Updated:

Hi,

Please upload your presentation for review by the Pycon India Team.

Thanks!

Gourav Chawla (~Gouravchawla)

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