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93250606
Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techn, (Paperback)
Item #:
93250606
NIO 1841
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Product Details
- 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.
| Manual & guide type | Instruction Manual |
| Book format | Paperback |
| Edition | 2nd Edition |
| Skill level | Advanced |
| Pages | 249 |
| Language | English |
| Brand | Sayan Mukhopadhyay |
| Pub date | 2022-11-26 |
| Author | Sayan Mukhopadhyay |
| Subgenre | Information Theory |
| Genre | Computing & Internet |
| Bisac subject heading | Computers |
| Series title | No Series |
| Dimensions | 6.14 x 0.56 x 9.21 in (15.6 x 1.4 x 23.4 cm) |
| Age group | Adult |
| Retail packaging | Single Piece |
| Original languages | English |
Product Description
Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techn, (Paperback)
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Customer Questions & Answers
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Question:
Who is this book intended for?
Answer: This book is designed for data scientists and software developers interested in data analytics. -
Question:
What key topics does this book cover?
Answer: It covers time series analysis, machine learning, cloud analytics, and architectural patterns. -
Question:
What programming language is used throughout the book?
Answer: The book primarily uses Python for advanced data analytics techniques.
Sayan Mukhopadhyay All Manuals & Guides Editorial Review
Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techniques is a comprehensive guide tailored for advanced users seeking to deepen their knowledge in data analytics using Python. This 2nd edition contains 249 pages filled with insightful content aimed at adults interested in computing and internet technologies. The author, Sayan Mukhopadhyay, covers various subjects including information theory, with a focus on both text and image classification methods. Readers can expect detailed architectural patterns and optimization techniques that are crucial for mastering data analytics.
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Pros
- Comprehensive guide for advanced users
- Covers text and image classification
- Includes architectural patterns
- Focus on optimization techniques
- Suitable for adult learners
Cons
- May be overly technical for beginners
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Features & Benefits
- Master advanced data analytics concepts with Python.
- Learn time series analysis, classifications, and clustering techniques.
- Dive into supervised, unsupervised, and reinforcement learning methodologies.
- Explore modern cloud platforms like GCP and AWS for data analytics.
- Understand architectural patterns and design principles in Python.
- Perfect for data scientists and software developers aiming to enhance their analytics skills.
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