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  Creating Maintainable APIs

  Creating Maintainable APIs ab 47.99 € als Taschenbuch: A Practical Case-Study Approach. 1st ed. Aus dem Bereich: Bücher, Ratgeber, Computer & Internet,

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  • Price: 47.99 EUR excl. shipping
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  Designing Maintainable Software

  Designing Maintainable Software ab 63.99 € als pdf eBook: . Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Computer & Internet,

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  • Price: 63.99 EUR excl. shipping
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  Designing Maintainable Software

  Designing Maintainable Software ab 63.99 € als Taschenbuch: Softcover reprint of the original 1st ed. 1999. Aus dem Bereich: Bücher, Ratgeber, Computer & Internet,

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  • Price: 63.99 EUR excl. shipping
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  Creating Maintainable APIs

  Creating Maintainable APIs ab 47.99 € als pdf eBook: A Practical Case-Study Approach. Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Computer & Internet,

  • Shop: hugendubel
  • Price: 47.99 EUR excl. shipping
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  Building Maintainable Software C# Edition

  Building Maintainable Software C# Edition ab 19.49 € als epub eBook: Ten Guidelines for Future-Proof Code. Aus dem Bereich: eBooks, Belletristik, Erzählungen,

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  • Price: 19.49 EUR excl. shipping
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  Building Maintainable Software Java Edition

  Building Maintainable Software Java Edition ab 19.49 € als epub eBook: Ten Guidelines for Future-Proof Code. Aus dem Bereich: eBooks, Belletristik, Erzählungen,

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  • Price: 19.49 EUR excl. shipping
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  Writing Maintainable Unit Tests

  Writing Maintainable Unit Tests ab 40.49 € als Taschenbuch: Mastering the art of loosely coupled unit tests. Aus dem Bereich: Bücher, Ratgeber, Computer & Internet,

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  • Price: 40.49 EUR excl. shipping
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  Supporting Maintainable Exception Handling with Explicit Channels

  Supporting Maintainable Exception Handling with Explicit Channels ab 78.99 € als Taschenbuch: A Novel Exception Handling Model for Building Robust and Modular Software Systems. Aus dem Bereich: Bücher, Ratgeber, Computer & Internet,

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  • Price: 78.99 EUR excl. shipping
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  The Definitive Guide to Catalyst: Writing Extensible Scalable and Maintainable Perl-Based Web Applications

  The Definitive Guide to Catalyst: Writing Extensible Scalable and Maintainable Perl-Based Web Applications ab 53.49 € als Taschenbuch: Writing Extensible Scalable and Maintainable Perl-Based Web Applications. New. Aus dem Bereich: Bücher, Ratgeber, Computer & Internet,

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  • Price: 53.49 EUR excl. shipping
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  Machine Learning Engineering in Action (eBook, ePUB)

  Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you'll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You'll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You'll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author's extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists familiar with supervised machine learning and the basics of object-orientaFor data scientists who know machine learning and the basics of object-oriented programming.ed programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer. Table of Contents PART 1 AN INTRODUCTION TO MACHINE LEARNING ENGINEERING 1 What is a machine learning engineer? 2 Your data science could use some engineering 3 Before you model: Planning and scoping a project 4 Before you model: Communication and logistics of projects 5 Experimentation in action: Planning and researching an ML project 6 Experimentation in action: Testing and evaluating a project 7 Experimentation in action: Moving from prototype to MVP 8 Experimentation in action: Finalizing an MVP with MLflow and runtime optimization PART 2 PREPARING FOR PRODUCTION: CREATING MAINTAINABLE ML 9 Modularity for ML: Writing testable and legible code 10 Standards of coding and creating maintainable ML code 11 Model measurement and why it's so important 12 Holding on to your gains by watching for drift 13 ML development hubris PART 3 DEVELOPING PRODUCTION MACHINE LEARNING CODE 14 Writing production code 15 Quality and acceptance testing 16 Production infrastructure

  • Shop: buecher
  • Price: 42.40 EUR excl. shipping

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