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The Machine Learning Solutions Architect Handbook. Create machine learning platforms to run solutions in an enterprise setting

(ebook) (audiobook) (audiobook) Książka w języku 1
Autor:
David Ping
The Machine Learning Solutions Architect Handbook. Create machine learning platforms to run solutions in an enterprise setting David Ping - okladka książki

The Machine Learning Solutions Architect Handbook. Create machine learning platforms to run solutions in an enterprise setting David Ping - okladka książki

The Machine Learning Solutions Architect Handbook. Create machine learning platforms to run solutions in an enterprise setting David Ping - audiobook MP3

The Machine Learning Solutions Architect Handbook. Create machine learning platforms to run solutions in an enterprise setting David Ping - audiobook CD

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Bądź pierwszym, który oceni tę książkę
Czas nagrania:
08:32:00
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Ebook (152,10 zł najniższa cena z 30 dni)

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Audiobook w mp3 (179,10 zł najniższa cena z 30 dni)

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Do przechowalni

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When equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you’ll need to become one.

You’ll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch.

Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You’ll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. And finally, you'll get acquainted with AWS AI services and their applications in real-world use cases.

By the end of this audiobook, you’ll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional.

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O autorze książki

David Ping is a senior technology leader with over 25 years of experience in the technology and financial services industry. His technology focus areas include cloud architecture, enterprise ML platform design, large-scale model training, intelligent document processing, intelligent media processing, intelligent search, and data platforms. He currently leads an AI/ML solutions architecture team at AWS, where he helps global companies design and build AI/ML solutions in the AWS cloud. Before joining AWS, David held various senior technology leadership roles at Credit Suisse and JPMorgan. He started his career as a software engineer at Intel. David has an engineering degree from Cornell University.

Packt Publishing - inne książki

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