You're reading from Engineering MLOps

Product typeBook

Published inApr 2021

PublisherPackt

ISBN-139781800562882

Edition1st Edition

Tools

Azure Functions

Concepts

Machine Learning

Author (1)

Emmanuel Raj

Tools and infrastructure

The MLOps landscape has been developing rapidly over the last two years; many tools and frameworks have evolved as part of the infrastructural offering. You can visit https://landscape.lfai.foundation/ to see how many mainstream options have been developed to orchestrate ML, deep learning, reinforcement learning, development environments, data pipelines, model management, explainable AI, security, and distributed computing.

There is a surge in services provided by popular cloud service providers such as Microsoft, AWS, and Google, which are complemented by data processing tools such as Airflow, Databricks, and Data Lake. These are crafted to enable ML and deep learning, for which there are great frameworks available such as scikit-learn, Spark MLlib, PyTorch, TensorFlow, MXNet, and CNTK, among others. Tools and frameworks are many, but procuring the right tools is a matter of choice and the context of your ML solution and operations setup. Having the right...

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Engineering MLOps

Published in: Apr 2021Publisher: PacktISBN-13: 9781800562882

Author (1)

Emmanuel Raj

Emmanuel Raj is a Finland-based Senior Machine Learning Engineer with 6+ years of industry experience. He is also a Machine Learning Engineer at TietoEvry and a Member of the European AI Alliance at the European Commission. He is passionate about democratizing AI and bringing research and academia to industry. He holds a Master of Engineering degree in Big Data Analytics from Arcada University of Applied Sciences. He has a keen interest in R&D in technologies such as Edge AI, Blockchain, NLP, MLOps and Robotics. He believes "the best way to learn is to teach", he is passionate about sharing and learning new technologies with others.
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