Keras

In this Keras Training covers essential modules to deliver skills in alignment with the current job market. This course will teach you how to use Keras to pre-process data, model, build, analyze, and optimize neural networks. You will learn how to organize data for the purpose of designing and training an artificial neural network from the ground up, how to develop and fine-tune CNNs (Convolutional Neural Networks), and deploy models. Our expert trainer community curates the curriculum to meet the standards of the latest certifications and skills employers expect from trained individuals.

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In this Keras Training covers essential modules to deliver skills in alignment with the current job market. This course will teach you how to use Keras to pre-process data, model, build, analyze, and optimize neural networks. You will learn how to organize data for the purpose of designing and training an artificial neural network from the ground up, how to develop and fine-tune CNNs (Convolutional Neural Networks), and deploy models. Our expert trainer community curates the curriculum to meet the standards of the latest certifications and skills employers expect from trained individuals.

 
Course Objectives:

In this course, you will learn to:

 
  • Fundamentals of Deep Learning and Neural Networks.
  • Understand Deep Learning with Keras.
  • Overview of Keras features and its advantages.
  • Keras Installation.
  • Keras Models, Layers, and Modules.
  • Keras's Neural Network Model Life-Cycle.
  • Using Keras, you may create your own neural network.
  • Creating a Multilayer Perceptron Neural Network.
  • Convolutional Neural Networks (CNNs) and its Layers.
  • Creating an Image Classification Model Using Keras.
 

Course content

 

Basic Overview of Keras
  • Understanding the features of Keras
  • Advantages of Keras
  • Keras Limitations
Keras Installation and API 
Installing Keras
  • Installation of dependencies
  • Installation of Theano
  • Installation of TensorFlow
  • Installation of Keras
  • Testing each Installation
Configuring Keras
  • Installation of Keras on Docker
  • Installation of Keras on Google Cloud ML
  • Installation of Keras on Amazon AWS
  • Installation of Keras on Microsoft Azure
Keras API
  • Basic Architecture of Keras
  • Overview of predefined neural network layers
  • Overview of predefined activation functions
  • Understanding Losses Functions
  • Understanding Metrics
  • Some Useful Operations
Overview of Deep Learning with ConvNets
  • Deep Convolutional Neural Network
  • Understanding Deep Convolutional Neural Network (DCNN)
  • Simple Example of DCNN
  • Recognizing CIFAR-10 images with DL
Concept of Generative Adversarial Networks and Wavenet
  • Overview of GAN
  • Keras adversarial GANs for forging MNIST
  • Keras adversarial GANs for forging CIFAR
  • Understanding WaveNet
Word Embeddings
  • Distributed Representations
  • Understanding word2vec
  • GloVe Exploring functionalities
  • Using pre-trained embeddings
Overview of Recurrent Neural Networks RNN
  • Basics of SimpleRNN cells
  • Understanding RNN Topologies
  • Using Gated Recurrent Unit -GRU
  • Concept of Bidirectional RNNs
  • Vanishing and exploding gradients
  • Using Long Short Term Memory -LSTM
  • Understanding Stateful RNNs
Additional Deep Learning Models
  • Dealing with Keras Functional API
  • Understanding Regression Networks
  • Concept of Unsupervised Learning
  • Keras Customization scenario
  • Using Generative Models

 

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Course Prerequisites

 
  • There are no prerequisites to learning the Keras Certification

Who can attend

 
  • Deep Learning / Machine Learning Engineers.
  • Data Scientists.
  • Beginners aspiring for a career in Keras.

Number of Hours: 30hrs

Certification

TensorFlow Developer Certificate

Key features

  • One to One Training
  • Online Training
  • Fastrack & Normal Track
  • Resume Modification
  • Mock Interviews
  • Video Tutorials
  • Materials
  • Real Time Projects
  • Virtual Live Experience
  • Preparing for Certification

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  • Online Training
  • Fastrack & Normal Track
  • Resume Modification
  • Mock Interviews
  • Video Tutorials
  • Materials
  • Real Time Projects
  • Materials
  • Preparing for Certification

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