• Books
  • AI and ML
  • MLOps
  • Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow
Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow
A

Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow

MLOps
TensorFlow MLOps machine learning pipelines TensorFlow Extended model lifecycle automation data validation production deployment
Author
Hannes Hapke, Catherine Nelson
Publisher
O’Reilly Media
Year
2020
Language
English
31
Rate this book

To read the book, log in / register

Preview fragment

Similar books

Neural Networks with TensorFlow and Keras: Training, Generative Models, and Reinforcement Learning

Neural Networks with TensorFlow and Keras: Training, Generative Models, and Reinforcement Learning

Philip Hua

Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python

Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python

Pramod Singh, Avinash Manure

Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Aurélien Géron

Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python

Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python

Hariom Tatsat, Sahil Puri, Brad Lookabaugh

TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

Bharath Ramsundar, Reza Bosagh Zadeh

Machine Learning Algorithms Using Scikit and TensorFlow Environments

Machine Learning Algorithms Using Scikit and TensorFlow Environments

Puvvadi Baby Maruthi, Smrity Prasad, Amit Kumar Tyagi

AI and ML for Coders in PyTorch: A Coder’s Guide to Generative AI and Machine Learning

AI and ML for Coders in PyTorch: A Coder’s Guide to Generative AI and Machine Learning

Laurence Moroney

Generative AI on Kubernetes: Operationalizing Large Language Models

Generative AI on Kubernetes: Operationalizing Large Language Models

Roland Huß, Daniele Zonca

Learning AutoML: Automating ML Pipelines with AutoGluon, Leading Frameworks, and Real-World Integration

Learning AutoML: Automating ML Pipelines with AutoGluon, Leading Frameworks, and Real-World Integration

Kerem Tomak

Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python, Second Edition

Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python, Second Edition

Shamshad Ansari