Course details

Deep Learning with Keras

Deep Learning with Keras


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

In this 19-video course, learners explore deep learning with Keras, including how to create and use neural networks with Keras for machine learning solutions. Begin with an overview of what neural networks are and their main components, followed by an introduction to Keras and its guiding principles. Observe how to configure Microsoft Cognitive Toolkit (CNTK) as your Keras backend; install and configure Keras; identify and work with both types of models available in Keras; and recognize features of commonly-used Keras layers and when to use them. Use Keras to make regression classifications and image classifications; Keras metrics to judge a model's performance; and Jupyter Notebooks with Keras. Next, download and load a data set from MNIST or CIFAR-10; explore data sets in Keras; prepare your data in Keras by defining input and target tensors, and compile the model in Keras. Then train and test your neural network; evaluate and score the performance of neural networks in Keras, and make predictions using your data set in Keras. The closing exercise involves using a neural network to make predictions.



Expected Duration (hours)
1.9

Lesson Objectives

Deep Learning with Keras

  • Course Overview
  • describe what neural networks are and their main components
  • describe Keras and its guiding principles
  • configure CNTK as your Keras backend
  • install and configure Keras
  • identify and work with both types of models available in Keras
  • recognize features of commonly used Keras layers and when to use them
  • use Keras to make regression classifications
  • use Keras to make image classifications
  • use Keras metrics to judge the performance of your model
  • use Jupyter Notebooks with Keras
  • download and load a dataset from MNIST or CIFAR-10
  • explore your dataset in Keras
  • prepare your data in Keras by defining your input and target tensors
  • compile the model in Keras
  • train and test your neural network
  • evaluate and score the performance of your neural network in Keras
  • make predictions using your dataset in Keras
  • use a neural network to make predictions
  • Course Number:
    it_mldlcvdj_01_enus

    Expertise Level
    Intermediate