Deep Learning with Keras Training

Deep Learning with Keras particularly written in Python Language primarily aims for creating Machine Learning Application capable of running on top of TensorFlow.

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Duration: 2 Days

Course fee:$399.00 (₹0)

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Product Description

Deep Learning with Keras Online Training focuses on implementation of Keras for fast and efficient deep-learning models. Neural Network library, Keras, generally deals with network library usually written in Python Programming Language. The training includes the installation and configuration of Keras using Docker, AWS and MS Azure. Keras generally focuses on the concepts related to the neural network layers specifically for the Deep Learning Applications. The training discusses functionalities of Generative Adversarial Networks and Wavenet specialized for Advanced Networking concepts. Keras when used in Deep Learning Application, the developers easily work on GloVe functionalities and sharing some innovative features on it. Basic information about Keras API is included in the training along with some predefined functions for the applications. On the completion of the training, the developers or aspirants can gain the knowledge on creating ML Application using Keras Library.

Objectives

  • Understanding the basic understanding of Keras and its implementation
  • Creation and Deployment of Blockchain Application in more secure manner
  • Implementation of Keras in future-scope for better Secure Application

Advantages

  • Capable of running on top of MXnet, Deeplearning4j
  • Expertise in delivering and deploying Blockchain Application more faster
  • Expertise in deep-learning models and practical use-cases

 

Additional Information

Day 1

1. Basic Overview of Keras

2. Understanding the features of Keras

3. Basic Installation of Keras

– Installation of dependencies
– Installation of Theano
– Installation of TensorFlow
– Installation of Keras
– Testing each Installation

4. Basic Configuration of 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

5. Understanding Keras API

– Basic Architecture of Keras
– Overview of predefined neural network layers
– Overview of predefined activation functions
– Understanding Losses Functions
– Understanding Metrics

6. Overview of Deep Learning with ConvNets

– Understanding Deep Convolutional Neural Network (DCNN)
– Simple Example of DCNN
– Recognizing CIFAR-10 images with DL

Day 2

1. Concept of Generative Adversarial Networks and Wavenet

– Overview of GAN
– Keras adversarial GANs for forging MNIST
– Keras adversarial GANs for forging CIFAR
– Understanding WaveNet

2. Deep Dive into Word Embeddings

– Understanding word2vec
– GloVe Exploring functionalities
– Using pre-trained embeddings

3. Overview of Recurrent Neural Networks RNN

– Basics of SimpleRNN cells
– Understanding RNN Topologies
– Vanishing and exploding gradients
– Using Long Short Term Memory -LSTM
– Using Gated Recurrent Unit -GRU
– Concept of Bidirectional RNNs
– Understanding Stateful RNNs

4. 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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