Integrate MLOps principles into existing or future projects using MLFlow operationalize your models and deploy them in AWS SageMaker Google Cloud and Microsoft Azure. This book guides you through the process of data analysis model construction and training. The au... Lees meer.

Deploying a machine learning model into a fully realized production system usually requires painstaking work by an operations team creating and managing custom servers. Cloud Native Machine Learning helps you bridge that gap by using the pre-built services provided by c... Lees meer.

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Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is and how it differs from De... Lees meer.

Design build and secure scalable machine learning ML systems to solve real-world business problems with Python and AWS Purchase of the print or Kindle book includes a free PDF eBook Key Features Go in-depth into the ML lifecycle from ideation and data management t... Lees meer.

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors three Google engineers catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns c... Lees meer.

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Supercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environments Key Features Explore hyperparameter optimization and model management tools Learn object-oriented programming and functional... Lees meer.

Implementing ML pipelines using MLOps KEY FEATURES In-depth knowledge of MLOps including recommendations for tools and processes. Includes only open-source cloud-agnostic tools for demonstrating MLOps. Covers end-to-end examples of implementing the whole... Lees meer.

What are evaluation criteria for the output. How do you engage the workforce in addition to satisfying them. How can you reduce costs. Are employees recognized for desired behaviors. Does the goal represent a desired result that can be measured. This premium Machin... Lees meer.

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Understand how to use MLOps as an engineering discipline to help with the challenges of bringing machine learning models to production quickly and consistently. This book will help companies worldwide to adopt and incorporate machine learning into their processes and pr... Lees meer.

Own your MLOps Risk with your MLOps resource. Be your own consultant. Your MLOps risk becomes your reward with this book and its accompanying digital resources. Cultivate an in-house knowledge base with the self-assessment that cuts out expensive consultants and gives... Lees meer.

Bew hrte Praxisl sungen f r komplexe Machine-Learning-Aufgaben Behandelt alle Phasen der ML-Produktpipeline Klar strukturierter Aufbau. Konzepte und Zusammenh nge erschlie en sich dadurch schnell Fokus auf TensorFlow aber auch bertragbar auf PyTorch-Projekte Die De... Lees meer.

More than half of the analytics and machine learning ML models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical but others are organizational. Either way the bottom line is that mod... Lees meer.