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What you'll get

  • Job Credibility
  • Certification Valid for Life
  • On-demand video*
  • E-Book
  • Self-Paced Learning
  • Certificate of Completion

Exam details

  • Mode of Exam : Online
  • Duration : 1 Hour
  • Multiple Choice Questions are asked
  • No. of Questions are asked : 50
  • Passing Marks : 25 (50%)
  • There is no negative marking

Do you want to learn Keras for deep learning? The course Deep Learning With Keras Certification is a certificate course that will help students to start learning Keras. This course basically introduces the basics to advanced of Deep Learning with Keras Library and helps students to understand what is Deep Learning, what is Keras, etc. After taking this certification, Students will be able to showcase their certificate to their resume and can also use it for further study.

This is the course where you will explore about basics of neural networks, understand deep learning models, and understand the Keras library. So after enrolling in this course you will be able to answer what is deep learning with Keras and what is its function. This can be great to enter virtual reality to build up a career path in deep learning.

Why should you join our Deep Learning With Keras course?

  • Our expert will explain to you each point about this wonderful application.
  • Also, you will learn neural networks from the basics.
  • Understand the vanishing gradient problems and regression methods
  • Exploring deep learning models, including recurrent neural networks.
  • All the basics to advanced topics are covered in this program

So, if you are a student who wants to learn deep learning from scratch then you can enroll in this job-ready course. After this course, you can move from advanced topics to deep learning when your basics get stronger. At the end of the course, you will get the test to take and after the successful full completion, you will receive a certificate that is valid all over the world. You can add this certificate to your CV to get the best career opportunities.

Course Content

Total: 52 lectures
  • Neural Networks Foundations
  • Perceptron
  • Multilayer perceptron — the first example of a network
  • A real example — recognizing handwritten digits
  • A practical overview of backpropagation
  • Towards a deep learning approach
  • Keras Installation and API
  • Installing Keras
  • Configuring Keras
  • Installing Keras on Docker
  • Installing Keras on Google Cloud ML
  • Installing Keras on Amazon AWS
  • Installing Keras on Microsoft Azure
  • Keras API
  • Callbacks for customizing the training process
  • Deep Learning with ConvNets
  • Deep convolutional neural network — DCNN
  • An example of DCNN — LeNet
  • Recognizing CIFAR-10 images with deep learning
  • Very deep convolutional networks for large-scale image recognition
  • Generative Adversarial Networks and WaveNet
  • What is a GAN?
  • Deep convolutional generative adversarial networks
  • Keras adversarial GANs for forging MNIST
  • Keras adversarial GANs for forging CIFAR
  • WaveNet — a generative model for learning how to produce audio
  • Word Embeddings
  • Distributed representations
  • word2vec
  • Exploring GloVe
  • Using pre-trained embeddings
  • Recurrent Neural Network — RNN
  • SimpleRNN cells
  • RNN topologies
  • Vanishing and exploding gradients
  • Long short term memory — LSTM
  • Gated recurrent unit — GRU
  • Bidirectional RNNs
  • Stateful RNNs
  • Other RNN variants
  • Additional Deep Learning Models
  • Keras functional API
  • Regression networks
  • Unsupervised learning — autoencoders
  • Composing deep networks
  • Customizing Keras
  • Generative models
  • AI Game Playing
  • Reinforcement learning
  • Example - Keras deep Q-network for catch
  • The road ahead
  • Conclusion


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