Deep Learning with Keras
Keras 2.2.4
| Intermediate
- 19 Videos | 1h 54m 50s
- Includes Assessment
- Earns a Badge
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.
WHAT YOU WILL LEARN
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describe what neural networks are and their main componentsdescribe Keras and its guiding principlesconfigure CNTK as your Keras backendinstall and configure Kerasidentify and work with both types of models available in Kerasrecognize features of commonly used Keras layers and when to use themuse Keras to make regression classificationsuse Keras to make image classificationsuse Keras metrics to judge the performance of your model
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use Jupyter Notebooks with Kerasdownload and load a dataset from MNIST or CIFAR-10explore your dataset in Kerasprepare your data in Keras by defining your input and target tensorscompile the model in Kerastrain and test your neural networkevaluate and score the performance of your neural network in Kerasmake predictions using your dataset in Kerasuse a neural network to make predictions
IN THIS COURSE
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1.Course Overview1m 39sUP NEXT
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2.Neural Networks7m 59s
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3.Introduction to Keras4m 4s
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4.Keras Backend7m 41s
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5.Set up Keras3m 51s
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6.Model Types in Keras9m 53s
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7.Keras Layers8m 40s
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8.Regression Classification5m 28s
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9.Image Classification7m 34s
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10.Keras Metrics4m 44s
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11.Jupyter Notebooks5m 23s
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12.Dataset for Neural Network4m 35s
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13.Explore Your Dataset5m 2s
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14.Data Preparation6m 47s
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15.Compiling the Model6m 55s
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16.Training and Testing Neural Networks5m 47s
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17.Evaluate the Model7m 7s
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18.Making Predictions5m 57s
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19.Exercise: Using a Neural Network5m 45s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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