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Data Science Workshop eBook

Learn How You Can Build Machine Learning Models And Create Your Own Real-World Data Science Projects

by Andrew Worsley, Anthony So, Dr. Samuel Asare, Robert Thas John e Thomas V. Joseph
language: english
Publisher: PACKT PUBLISHING, August of 2020 ‧
35,76€
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Ebook for ADE
Key Features
  • Gain a full understanding of the model production and deployment process
  • Build your first machine learning model in just five minutes and get a hands-on machine learning experience
  • Understand how to deal with common challenges in data science projects
    • What you will learn

    • Explore the key differences between supervised learning and unsupervised learning
    • Manipulate and analyze data using scikit-learn and pandas libraries
    • Understand key concepts such as regression, classification, and clustering
    • Discover advanced techniques to improve the accuracy of your model
    • Understand how to speed up the process of adding new features
    • Simplify your machine learning workflow for production
      • Who this book is for

        This is one of the most useful data science books for aspiring data analysts, data scientists, database engineers, and business analysts. It is aimed at those who want to kick-start their careers in data science by quickly learning data science techniques without going through all the mathematics behind machine learning algorithms. Basic knowledge of the Python programming language will help you easily grasp the concepts explained in this book.]]>

Data Science Workshop

Learn How You Can Build Machine Learning Models And Create Your Own Real-World Data Science Projects

by Andrew Worsley, Anthony So, Dr. Samuel Asare, Robert Thas John e Thomas V. Joseph

Property Description
ISBN: 9781800569409
Publisher: PACKT PUBLISHING
Release Date: August of 2020
Language: English
Format: eBook
File Format and Compatibility:
Categories: eBooks in English > Computing > Schedule
eBooks in English > Others
EAN: 9781800569409
Acessibilidade: Ver características de acessibilidade indicadas pelo editor