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Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow

Name: Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow
Price: 38.49 USD
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4.5 of 5 Stars: Databases & Big Data - Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow

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Book Synopsis: Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps that make up a machine learning pipeline, build your pipeline using components from TensorFlow Extended, orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines, work with data using TensorFlow Data Validation and TensorFlow Transform, analyze a model in detail using TensorFlow Model Analysis, examine fairness and bias in your model performance, deploy models with TensorFlow Serving or convert them to TensorFlow Lite for mobile devices, understand privacy-preserving machine learning techniques. Read more

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Are you tired of wasting time and money on machine learning projects that don't get deployed effectively? Look no further! Introducing "Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow" - a practical guide by Hannes Hapke and Catherine Nelson that will revolutionize the way you develop and deploy machine learning models.

With the techniques and tools shared in this book, you can cut down deployment time from days to minutes, enabling you to focus on what really matters - developing new models. This means you can stay ahead of the competition by delivering faster, more efficient solutions that meet your business needs.

Whether you're a data scientist, machine learning engineer, DevOps engineer or manager, this book can help you take your data science projects to the next level. Gain a deep understanding of the machine learning pipeline and learn how to build your own using components from TensorFlow Extended. Seamlessly orchestrate your pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines to streamline the entire process.

But it doesn't stop there. "Building Machine Learning Pipelines" also teaches you how to work with data using TensorFlow Data Validation and TensorFlow Transform. Analyze your models in detail with TensorFlow Model Analysis and ensure fairness and bias-free performance. Plus, discover how to deploy your models using TensorFlow Serving or convert them to TensorFlow Lite for mobile devices.

What's more, the book touches on privacy-preserving machine learning techniques, equipping you with the knowledge to protect sensitive data and comply with regulations.

Don't miss out on this opportunity to revolutionize your machine learning projects and accelerate your success. Get your copy of "Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow" today!

Ready to take your machine learning projects to the next level? Get "Building Machine Learning Pipelines" now: Buy Now

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