Deep Learning in R

Deep Learning in R

Training description

Machine Learning changes the business reality rapidly. Deep Learning became the main driver of this revolution. Thanks to Deep Learning, such things as speech recognition or computer vision become not only possible but also extremely effective.

“Deep Learning in R” is an advanced training dedicated to everyone who would like to learn how to build powerful models in R powered by Deep Neural Networks.

Duration: 3 days 8 hours each (including an hour lunch break)

Extended version is also available – 4 days 8 hours each.

Requirements: knowledge of R programming language at an intermediate level (especially in data processing field).

Training agenda

Part one: Let’s get it started!

  • What’s Deep Learning?
  • Machine Learning vs. Deep Learning
  • Algorithms overview

Part two: The necessary foundation

  • Introduction to Neural network
  • Types of activation functions
  • Backpropagation method
  • Gradient Descent vs. Stochastic Gradient Descent
  • Overfitting
  • Model validation

Part three: Write it by yourself!

  • Building deep neural networks
  • Building models by Keras

Part four: An infinity of possibilities

  • Convolutional Neural Networks (CNN)
  • Recurrent Neural Networks (RNN)
  • How to build neural network for structured data – Entity Embeddings

Part five: In search of best solution…

  • Regularization
  • Hyperparameter tuning

Upcoming open trainings

Currently, no open training covering the given issue is planned. We encourage you to contact us regarding the closed training.

Contact us about closed training
Go to open training base

This website uses cookies to ensure you get the best experience on our website.
Ok, got it. More about cookies