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Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analyticswith reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application.
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Title: Advanced Data Analytics Using Python: With ...
Publisher: Apress
Publication Date: 2022
Binding: paperback
Condition: New
Edition: 2nd ed.
Seller: Lakeside Books, Benton Harbor, MI, U.S.A.
Condition: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books! Seller Inventory # OTF-S-9781484280041
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Paperback or Softback. Condition: New. Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techniques 0.84. Book. Seller Inventory # BBS-9781484280041
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: Rarewaves USA, OSWEGO, IL, U.S.A.
Paperback. Condition: New. 2nd ed. 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 analyticswith reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. What You'll LearnBuild intelligent systems for enterpriseReview time series analysis, classifications, regression, and clusteringExplore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analyticsUnderstand Covers design patterns in Python Who This Book Is ForData scientists and software developers interested in the field of data analytics. Seller Inventory # LU-9781484280041
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