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Advanced data analytics using Pythonwith architectural patterns, text and image classification, and optimization techniques /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced data analytics using Pythonby Sayan Mukhopadhyay, Pratip Samanta.
其他題名:	with architectural patterns, text and image classification, and optimization techniques /
作者:	Mukhopadhyay, Sayan.
其他作者:	Samanta, Pratip.
出版者:	Berkeley, CA :Apress :2023.
面頁冊數:	xvii, 249 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Python (Computer program language)
電子資源:	https://doi.org/10.1007/978-1-4842-8005-8
ISBN:	9781484280058$q(electronic bk.)

Advanced data analytics using Pythonwith architectural patterns, text and image classification, and optimization techniques /
Mukhopadhyay, Sayan.

Advanced data analytics using Pythonwith architectural patterns, text and image classification, and optimization techniques /[electronic resource] :by Sayan Mukhopadhyay, Pratip Samanta. - Second edition. - Berkeley, CA :Apress :2023. - xvii, 249 p. :ill., digital ;24 cm.

Chapter 1: Overview of Python Language -- Chapter 2: ETL with Python -- Chapter 3: Supervised Learning and Unsupervised Learning with Python -- Chapter 4: Clustering with Python -- Chapter 5: Deep Learning & Neural Networks -- Chapter 6: Time Series Analysis -- Chapter 7: Analytics in Scale.

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. You will: 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.

ISBN: 9781484280058$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-8005-8doiSubjects--Topical Terms:

215247
Python (Computer program language)

LC Class. No.: QA76.73.P98 / M85 2023

Dewey Class. No.: 005.133

Advanced data analytics using Pythonwith architectural patterns, text and image classification, and optimization techniques /
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