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Advanced Data Analytics Using Python

With Architectural Patterns, Text and Image Classification, and Optimization Techniques

Language EnglishEnglish
Book Paperback
Book Advanced Data Analytics Using Python Mukhopadhyay
Libristo code: 39332475
Publishers APress, November 2022
Understand advanced data analytics concepts such as time series and principal component analysis wit... Full description
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Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment.

Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. 

Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. 

What You'll Learn
  • Build intelligent systems for enterprise
  • Review time series analysis, classifications, regression, and clustering
  • Explore supervised learning, unsupervised learning, reinforcement learning, and transfer learning 
  • Use cloud platforms like GCP and AWS in data analytics
  • Understand Covers design patterns in Python 
Who This Book Is For

Data scientists and software developers interested in the field of data analytics.

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About the book

Full name Advanced Data Analytics Using Python
Language English
Binding Book - Paperback
Date of issue 2022
Number of pages 249
EAN 9781484280041
ISBN 1484280040
Libristo code 39332475
Publishers APress
Weight 412
Dimensions 234 x 154 x 20
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