Designing deep learning systems:
A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems...
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
[Place of publication not identified]
Manning Publications
2023
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781633439863AU/?ar |
| Zusammenfassung: | A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning's design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting--and lucrative--career as a deep learning engineer. Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO. |
| Beschreibung: | Online resource; title from title details screen (O'Reilly, viewed February 05, 2024) |
| Umfang: | 1 Online-Ressource (1 audio file) |
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| 520 | |a A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning's design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting--and lucrative--career as a deep learning engineer. Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO. | ||
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| spelling | Wang, Chi VerfasserIn aut Designing deep learning systems Chi Wang, Donald Szeto [Place of publication not identified] Manning Publications 2023 1 Online-Ressource (1 audio file) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; title from title details screen (O'Reilly, viewed February 05, 2024) A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning's design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting--and lucrative--career as a deep learning engineer. Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO. Deep learning (Machine learning) Machine learning Apprentissage profond Apprentissage automatique Audiobooks Livres audio Szeto, Donald VerfasserIn aut |
| spellingShingle | Wang, Chi Szeto, Donald Designing deep learning systems Deep learning (Machine learning) Machine learning Apprentissage profond Apprentissage automatique Audiobooks Livres audio |
| title | Designing deep learning systems |
| title_auth | Designing deep learning systems |
| title_exact_search | Designing deep learning systems |
| title_full | Designing deep learning systems Chi Wang, Donald Szeto |
| title_fullStr | Designing deep learning systems Chi Wang, Donald Szeto |
| title_full_unstemmed | Designing deep learning systems Chi Wang, Donald Szeto |
| title_short | Designing deep learning systems |
| title_sort | designing deep learning systems |
| topic | Deep learning (Machine learning) Machine learning Apprentissage profond Apprentissage automatique Audiobooks Livres audio |
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