"Hands-On Data Science and Python Machine Learning" - Information and Links:

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Perform Data Mining and Machine Learning Efficiently Using Python and Spark

"Hands-On Data Science and Python Machine Learning" was published by de Gruyter GmbH, Walter in 2017 - Place of publication not identified, it has 1 pages and the language of the book is English.


“Hands-On Data Science and Python Machine Learning” Metadata:

  • Title: ➤  Hands-On Data Science and Python Machine Learning
  • Author:
  • Language: English
  • Number of Pages: 1
  • Publisher: de Gruyter GmbH, Walter
  • Publish Date:
  • Publish Location: ➤  Place of publication not identified

Edition Specifications:

  • Pagination: 420

Edition Identifiers:

AI-generated Review of “Hands-On Data Science and Python Machine Learning”:


"Hands-On Data Science and Python Machine Learning" Description:

Open Data:

Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis

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