Hands-On Unsupervised Learning Using Python (O'Reilly)
Monday, 15 April 2019

With a subtitle of "How to Build Applied Machine Learning Solutions from Unlabeled Data", this book shows how unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow - using Keras with hands-on examples and code. He shows how to identify difficult-to-find patterns in data, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets.

 

Author: Ankur A. Patel
Publisher: O'Reilly
Date: March 2019
Pages: 362
ISBN: 978-1492035640
Print: 1492035645
Kindle: B07NY447H8
Audience: Python developers interested in machine learning
Level: Intermediate
Category: Artificial Intelligence and Python

 

  • Compare the strengths and weaknesses of the different machine learning approaches: supervised, unsupervised, and reinforcement learning
  • Set up and manage a machine learning project end-to-end - everything from data acquisition to building a model and implementing a solution in production
  • Use dimensionality reduction algorithms to uncover the most relevant information in data and build an anomaly detection system to catch credit card fraud
  • Apply clustering algorithms to segment users - such as loan borrowers - into distinct and homogeneous groups
  • Use autoencoders to perform automatic feature engineering and selection
  • Combine supervised and unsupervised learning algorithms to develop semi-supervised solutions
  • Build movie recommender systems using restricted Boltzmann machines
  • Generate synthetic images using deep belief networks and generative adversarial networks
  • Perform clustering on time series data such as electrocardiograms
  • Explore the successes of unsupervised learning to date and its promising future

 

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

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SQL Server Advanced Troubleshooting and Performance Tuning (O'Reilly)

Author: Dmitri Korotkevitch
Publisher: O'Reilly
Pages: 497
ISBN: 978-1098101923
Print:1098101928
Kindle: B0B197NYD7
Audience: DBAs & database devs
Rating: 5
Reviewer: Ian Stirk

This book aims to improve the performance of your SQL Servers, how does it fare?



Software Development Pearls

Author: Karl Wiegers
Publisher: Addison-Wesley Professional
Pages: 336
ISBN: 978-0137487776
Print: 0137487770
Kindle: B09BF6CS9T
Audience: General developers
Rating: 2
Reviewer: Ian Elliot
Who can resist a good pearl or two?


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