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Data Science from Scratch: Comprehensive guide with essential principles of Data Science (Beginner's guide)

Data Science from Scratch: Comprehensive guide with essential principles of Data Science (Beginner's guide)

Data Science from Scratch: Comprehensive guide with essential principles of Data
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Data Science from Scratch: Comprehensive guide with essential principles of Data Science (Beginner's guide) Paperback - 2018

by Harvey, Scott

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  • Title Data Science from Scratch: Comprehensive guide with essential principles of Data Science (Beginner's guide)
  • Author Harvey, Scott
  • Binding Paperback
  • Condition New
  • Pages 110
  • Volumes 1
  • Language ENG
  • Publisher Createspace Independent Publishing Platform
  • Publication date 2018-05-09
  • Bookseller's Inventory # 33353099
  • ISBN 9781718726697 / 1718726694
  • Weight 0.35 lbs (0.16 kg)
  • Dimensions 9.02 x 5.98 x 0.23 in (22.91 x 15.19 x 0.58 cm)
  • Category Computers - General Information
  • Quantity available 5

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From the publisher

Read for FREE with Kindle Unlimited! Data Science from Scratch: Comprehensive guide with essential principles of Data Science (Beginner's guide) Do you want to learn data Science from scratch? Data is a commodity, but without ways to process it, its value is questionable. Data science is a multidisciplinary field whose goal is to extract value from data in all it's forms. This ebook explores the field of data science through data and its structure as well as the high-level process that you can use to transform data into value. Data science is a process. That's not to say it's mechanical and void of creativity. But, when you dig into the stages of processing data, from munging data sources and data cleansing to machine learning and eventually visualisation, you see that unique steps are involved in transforming raw data into insight. The steps that you use can also vary. In exploratory data analysis, you might have a cleansed data set that's ready to import into R, and you visualise your result but don't deploy the model in a production environment. In another environment, you might be dealing with real-world data and require a process of data merging and cleansing in addition to data scaling and preparation before you can train your machine learning model. Here Is A Preview Of What You'll Learn...
  • What is data science ?
  • What is structured data?
  • The data science process
  • Basic course on Python
  • How to run Python on your computer?
  • Explore the machine learning landscape, particularly neural nets
  • Explore recommender systems, natural language processing, network analysis
  • Much, much more!
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