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Deep Learning with R

( Duration: 5 Days )

The Deep Learning with R training course will teach to leverage deep learning to make sense of raw data by exploring various hidden layers. You will understand the basics of Deep Learning and move on to exploring advanced ANN's and RNN's. They will also dive into CNNs and Unsupervised Learning. You will also learn about the applications of Deep Learning in various fields and understand the practical implementations of deep learning models for scalability, high performance computing and feature engineering.

By attending Deep Learning with R workshop, delegates will learn:

  • Getting started with neural networks
  • Deep learning for computer vision
  • Deep learning for text and sequences

  • Basic R knowledge is assumed
  • Data Scientists
  • Data Analysts
  • Engineers



Getting Started on R Keras

  • What is Deep Learning ?
  • What is Keras
  • Why Using R Keras Package
  • Install R Keras Package

Neural Networks

  • What is Neural Network
  • Activation Functions
  • Neural Network on MNIST

Convolutional Neural Network

  • What is CNN?
  • CNN Architecture
  • Convolution Layers
  • Pooling and Dropout Layers
  • CNN on MNIST dataset

Transfer Learning

  • What is Transfer Learning
  • Pre-Trained Image Recognition Models
  • Fine Tuning Pre-Trained Models

Recurrent Neural Network

  • Sequential Data
  • What is RNN?
  • Types of RNN
  • How to train a RNN
  • Long Term Dependencies
  • LSTM and GRU Cells
  • RNN on IMDB datasets

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 6,000 various courses on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

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Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.