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Python machine learning / Wei-Meng Lee.

By: Publisher: Indianapolis, IN : John Wiley and Sons, 2019Copyright date: c2019Description: xxiv, 296 pages ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781119545637 (pbk)
Subject(s): DDC classification:
  • 005.133 .L482 2019
Summary: "Machine learning is a hot topic today, due in no small part to the rapid increase in computing power that allows a host of tasks to be performed on a desktop machine. However, machine learning can be overwhelming to the inexperienced. That's why Python Machine Learning provides a step-by-step approach that first educates you on the underlying technologies, enabling you to build on that knowledge base as you develop your machine learning skills. Python Machine Learning covers: - Fundamentals libraries used in Python to enable machine learning: Numpy, Pandas, and matplotlib - Common machine learning algorithms including regression, classification, clustering, and anomaly detection - Machine learning using Python and the Scikit-Learn libraries - Deploying machine learning models as web services - Machine learning using Microsoft Azure Machine Learning Studio - Real-world examples showing how machine learning creates solutions" --Provided by publisher
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Item type Current library Collection Call number Status Date due Barcode
Print Materials Main Library Engineering Non-fiction 005.133 .L482 2019 (Browse shelf(Opens below)) Available 0123693

Includes index

"Machine learning is a hot topic today, due in no small part to the rapid increase in computing power that allows a host of tasks to be performed on a desktop machine. However, machine learning can be overwhelming to the inexperienced. That's why Python Machine Learning provides a step-by-step approach that first educates you on the underlying technologies, enabling you to build on that knowledge base as you develop your machine learning skills.

Python Machine Learning covers:

- Fundamentals libraries used in Python to enable machine learning: Numpy, Pandas, and matplotlib
- Common machine learning algorithms including regression, classification, clustering, and anomaly detection
- Machine learning using Python and the Scikit-Learn libraries
- Deploying machine learning models as web services
- Machine learning using Microsoft Azure Machine Learning Studio
- Real-world examples showing how machine learning creates solutions" --Provided by publisher

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