Keras is an open source neural network library written in Python. It is capable of running on top of MXNet, Deeplearning4j, Tensorflow, CNTK, or Theano. Designed to enable fast experimentation with deep neural networks, it focuses on being minimal, modular, and extensible.

Why should one take Deep Learning with Keras Certification?

This Course is intended for Individuals wanting to understand a deeper level of deep learning using Keras. The course provides you a comprehensive introduction to deep learning, you will also be trained on neural networks and optimization techniques.

Earning Vskills Deep Learning with Keras Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.


Who will benefit from taking Deep Learning with Keras Certification?

IT specialists aspiring to learn a new skill set; statisticians; computer scientists; and IT analysts etc.


Companies that hire Vskills Certified Deep Learning with Keras Professional

Data Science with Python is one of the faster growing filed and are in great demand. Companies like KPMG, Accenture, TCS & Cognizant specializing in Data Science related activities are constantly looking for certified professionals.


Deep Learning with Keras Table of Contents

https://www.vskills.in/certification/deep-learning-with-keras-table-of-contents

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Table of Content


Module 1

NEURAL NETWORKS FOUNDATIONS

  • The Course Overview
  • Perceptron
  • Building a Network to Recognize Handwritten Numbers
  • Playing Around with the Parameters to Improve Performance

KERAS INSTALLATION AND API

  • Installing and Configuring Keras
  • Keras API
  • Callbacks for Customizing the Training Process

DEEP LEARNING WITH CONVOLUTIONAL NETWORKS

  • Deep Convolutional Neural Network - DCNN
  • Recognizing CIFAR-10 Images with Deep Learning


Module 2

INTRODUCTION TO DEEP LEARNING

  • The Course Overview
  • What is Deep Learning?
  • Machine Learning Concepts
  • Foundations of Neural Networks
  • Optimization

GET STARTED WITH KERAS

  • Configuration of Keras
  • Presentation of Keras and Its API
  • Design and Train Deep Neural Networks
  • Regularization in Deep Learning

CONVOLUTIONAL AND RECURRENT NEURAL NETWORKS

  • Introduction to Computer Vision
  • Convolutional Networks
  • CNN Architectures
  • Image Classification Example
  • Image Segmentation Example
  • Introduction to Recurrent Networks
  • Recurrent Neural Networks
  • “One to Many” Architecture
  • “Many to One” Architecture
  • “Many to Many” Architecture
  • Embedding Layers

RECOMMENDER SYSTEMS

  • What are Recommender Systems?
  • Content/Item Based Filtering
  • Collaborative Filtering
  • Hybrid System

NEURAL STYLE TRANSFER

  • Introduction to Neural Style Transfer
  • Single Style Transfer
  • Advanced Techniques
  • Style Transfer Explained

ADVANCED TECHNIQUES

  • Data Augmentation
  • Transfer Learning
  • Hyper-Parameter Search
  • Natural Language Processing

GENERATIVE ADVERSARIAL NETWORKS

  • An Introduction to Generative Adversarial Networks (GAN)
  • Run Our First GAN
  • Deep Convolutional Generative Adversarial Networks (DCGAN)
  • Techniques to Improve GANs
“Exam scheduling to be done through user account” / “Exam once scheduled cannot be cancelled”
Date of Examination
05-Oct-2019
06-Oct-2019
19-Oct-2019
20-Oct-2019
02-Nov-2019
03-Nov-2019
16-Nov-2019
17-Nov-2019
07-Dec-2019
08-Dec-2019
21-Dec-2019
22-Dec-2019
Examination Time
01:00 PM - 02:00 PM
02:30 PM - 03:30 PM
04:00 PM - 05:00 PM
05:30 PM - 06:30 PM
10:00 AM - 11:00 AM
11:30 AM - 12:30 PM

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Tags: Deep learning with keras, deep learning, Keras, Data Science