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  3. Machine learning

Advanced Data Analytics Using Python

- With Architectural Patterns, Text and Image Classification, and Optimization Techniques
Af: Sayan Mukhopadhyay, Pratip Samanta Engelsk Paperback

Advanced Data Analytics Using Python

- With Architectural Patterns, Text and Image Classification, and Optimization Techniques
Af: Sayan Mukhopadhyay, Pratip Samanta Engelsk Paperback
Tjek vores konkurrenters priser
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.
Vis mere
Tjek vores konkurrenters priser
Normalpris
kr 431
Fragt: 39 kr
6 - 8 hverdage
20 kr
Pakkegebyr
God 4 anmeldelser på
Tjek vores konkurrenters priser
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.
Vis mere
Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 249
ISBN-13: 9781484280041
Indbinding: Paperback
Udgave:
ISBN-10: 1484280040
Kategori: Machine learning
Udg. Dato: 26 nov 2022
Længde: 20mm
Bredde: 234mm
Højde: 154mm
Forlag: APress
Oplagsdato: 26 nov 2022
Forfatter(e): Sayan Mukhopadhyay, Pratip Samanta
Forfatter(e) Sayan Mukhopadhyay, Pratip Samanta

Kategori Machine learning

ISBN-13 9781484280041

Sprog Engelsk

Indbinding Paperback

Sider 249

Udgave

Længde 20mm

Bredde 234mm

Højde 154mm

Udg. Dato 26 nov 2022

Oplagsdato 26 nov 2022

Forlag APress

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