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You're reading from  The Deep Learning with Keras Workshop

Product typeBook
Published inJul 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781800562967
Edition1st Edition
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Authors (3):
Matthew Moocarme
Matthew Moocarme
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Matthew Moocarme

Matthew Moocarme is an accomplished data scientist with more than eight years of experience in creating and utilizing machine learning models. He comes from a background in the physical sciences, in which he holds a Ph.D. in physics from the Graduate Center of CUNY. Currently, he leads a team of data scientists and engineers in the media and advertising space to build and integrate machine learning models for a variety of applications. In his spare time, Matthew enjoys sharing his knowledge with the data science community through published works, conference presentations, and workshops.
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Mahla Abdolahnejad
Mahla Abdolahnejad
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Mahla Abdolahnejad

Mahla Abdolahnejad is a Ph.D. candidate in systems and computer engineering with Carleton University, Canada. She also holds a bachelor's degree and a master's degree in biomedical engineering, which first exposed her to the field of artificial intelligence and artificial neural networks, in particular. Her Ph.D. research is focused on deep unsupervised learning for computer vision applications. She is particularly interested in exploring the differences between a human's way of learning from the visual world and a machine's way of learning from the visual world, and how to push machine learning algorithms toward learning and thinking like humans.
Read more about Mahla Abdolahnejad

Ritesh Bhagwat
Ritesh Bhagwat
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Ritesh Bhagwat

Ritesh Bhagwat has a master's degree in applied mathematics with a specialization in computer science. He has over 14 years of experience in data-driven technologies and has led and been a part of complex projects ranging from data warehousing and business intelligence to machine learning and artificial intelligence. He has worked with top-tier global consulting firms as well as large multinational financial institutions. Currently, he works as a data scientist. Besides work, he enjoys playing and watching cricket and loves to travel. He is also deeply interested in Bayesian statistics.
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3. Deep Learning with Keras

Activity 3.01: Building a Single-Layer Neural Network for Performing Binary Classification

In this activity, we will compare the results of a logistic regression model and single-layer neural networks of different node sizes and different activation functions. The dataset we will use represents the normalized test results of aircraft propeller inspections, while the class represents whether they passed or failed a manual visual inspection. We will create models to predict the results of the manual inspection when given the automated test results. Follow these steps to complete this activity:

  1. Load all the required packages:
    # import required packages from Keras
    from keras.models import Sequential 
    from keras.layers import Dense, Activation 
    import numpy as np
    import pandas as pd
    from tensorflow import random
    from sklearn.model_selection import train_test_split
    # import required packages for plotting
    import matplotlib.pyplot as plt 
    import matplotlib...
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The Deep Learning with Keras Workshop
Published in: Jul 2020Publisher: PacktISBN-13: 9781800562967

Authors (3)

author image
Matthew Moocarme

Matthew Moocarme is an accomplished data scientist with more than eight years of experience in creating and utilizing machine learning models. He comes from a background in the physical sciences, in which he holds a Ph.D. in physics from the Graduate Center of CUNY. Currently, he leads a team of data scientists and engineers in the media and advertising space to build and integrate machine learning models for a variety of applications. In his spare time, Matthew enjoys sharing his knowledge with the data science community through published works, conference presentations, and workshops.
Read more about Matthew Moocarme

author image
Mahla Abdolahnejad

Mahla Abdolahnejad is a Ph.D. candidate in systems and computer engineering with Carleton University, Canada. She also holds a bachelor's degree and a master's degree in biomedical engineering, which first exposed her to the field of artificial intelligence and artificial neural networks, in particular. Her Ph.D. research is focused on deep unsupervised learning for computer vision applications. She is particularly interested in exploring the differences between a human's way of learning from the visual world and a machine's way of learning from the visual world, and how to push machine learning algorithms toward learning and thinking like humans.
Read more about Mahla Abdolahnejad

author image
Ritesh Bhagwat

Ritesh Bhagwat has a master's degree in applied mathematics with a specialization in computer science. He has over 14 years of experience in data-driven technologies and has led and been a part of complex projects ranging from data warehousing and business intelligence to machine learning and artificial intelligence. He has worked with top-tier global consulting firms as well as large multinational financial institutions. Currently, he works as a data scientist. Besides work, he enjoys playing and watching cricket and loves to travel. He is also deeply interested in Bayesian statistics.
Read more about Ritesh Bhagwat