Tag: Data Processing

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Models and Algorithms for Unlabelled Data Front Cover

Models and Algorithms for Unlabelled Data

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Apache Kafka in Action: From basics to production Front Cover

Apache Kafka in Action: From basics to production

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Automotive Software Architectures: An Introduction Front Cover

Automotive Software Architectures: An Introduction

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Automotive Software Architectures: An Introduction, 2nd Edition Front Cover

Automotive Software Architectures: An Introduction, 2nd Edition

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JavaScript for Data Science Front Cover

JavaScript for Data Science

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Machine Learning for Algorithmic Trading, 2nd Edition: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python Front Cover

Machine Learning for Algorithmic Trading, 2nd Edition: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python

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Hands-On Machine Learning for Algorithmic Trading Front Cover

Hands-On Machine Learning for Algorithmic Trading

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Practical MATLAB Deep Learning: A Projects-Based Approach, 2nd Edition Front Cover

Practical MATLAB Deep Learning: A Projects-Based Approach, 2nd Edition

  • Length: 348 pages
  • Publication Date: 2022-09-25
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Practical Microsoft Azure IaaS: Migrating and Building Scalable and Secure Cloud Solutions Front Cover

Practical Microsoft Azure IaaS: Migrating and Building Scalable and Secure Cloud Solutions

  • Length: 325 pages
  • Publication Date: 2018-07-21
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Fundamentals of Data Engineering: Plan and Build Robust Data Systems Front Cover

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

  • Length: 424 pages
  • Publication Date: 2022-08-02
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Advanced Analytics with PySpark: Patterns for Learning from Data at Scale Using Python and Spark Front Cover

Advanced Analytics with PySpark: Patterns for Learning from Data at Scale Using Python and Spark

  • Length: 275 pages
  • Publication Date: 2022-05-17
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Data Quality Fundamentals: A Practitioner’s Guide to Building Trustworthy Data Pipelines Front Cover

Data Quality Fundamentals: A Practitioner’s Guide to Building Trustworthy Data Pipelines

  • Length: 308 pages
  • Publication Date: 2022-10-18
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