Large-Scale Data Analytics with Python and Spark A Hands-on Guide to Implementing Machine Learning Solutions
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Description
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,…
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Key features
- Engages students and supports instructors in teaching large-scale data analytics and ML
- Encourages hands-on learning and fosters reflective thinking with explanations, code, real examples, and exam-style exercises
- Introduces the key principles of big data platforms rather than attempting to cover all technical aspects, to avoid overwhelming students
- Provides lab assignments to assess student progress, designed to run on standard computers without expensive big data infrastructures
Keywords
About the book
- DOI https://doi.org/10.1017/9781009318242
- Subjects Computer Science,Data Science, Databases, Data Mining, and Information Retrieval,Machine Learning and Pattern Recognition
- Format: Paperback
- Publication date: 08 February 2024
- ISBN: 9781009318259
- Dimensions (mm): 244 x 170 mm
- Weight: 0.78kg
- Page extent: 422 pages
- Availability: In stock
- Format: Digital
- Publication date: 15 December 2023
- ISBN: 9781009318242
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