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Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techniques [2nd Edition] by Sayan Mukhopadhyay, Pratip Samanta is a nonfiction available to read on EtoBox.
What is Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techniques [2nd Edition] about?
--CONVERTED PDF--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 cluste
Who reads Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techniques [2nd Edition]?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Sayan Mukhopadhyay, Pratip Samanta
- Publisher
- Apress L. P.; Apress
- Published
- 2022
- Language
- EN
- ISBN
- 9781484280041
- Category
- nonfiction
- Subjects
- Computer Science, Mathematics, Language Learning
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