Based on the authors' extensive teaching experience, this hands-on
graduate-level textbook teaches how to carry out large-scale data
analytics and design machine learning solutions for big data. With
a focus on fundamentals, this extensively class-tested textbook
walks students through key principles and paradigms for working
with large-scale data, frameworks for large-scale data analytics
(Hadoop, Spark), and explains how to implement machine learning to
exploit big data. It is unique in covering the principles that
aspiring data scientists need to know, without detail that can
overwhelm. Real-world examples, hands-on coding exercises and labs
combine with exceptionally clear explanations to maximize student
engagement. Well-defined learning objectives, exercises with online
solutions for instructors, lecture slides, and an accompanying
suite of lab exercises of increasing difficulty in Jupyter
Notebooks offer a coherent and convenient teaching package. An
ideal teaching resource for courses on large-scale data analytics
with machine learning in computer/data science departments.
General
| Imprint: |
Cambridge UniversityPress
|
| Country of origin: |
United Kingdom |
| Release date: |
November 2023 |
| Authors: |
Isaac Triguero
• Mikel Galar
|
| Pages: |
422 |
| ISBN-13: |
978-1-00-931825-9 |
| Categories: |
Books
Promotions
|
| LSN: |
1-00-931825-X |
| Barcode: |
9781009318259 |
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