Super VAI, ‘Silicon Valley’s ML Ops’ e-book translated into Korean and distributed free


Super VAI has announced that it will translate the ‘MILOps of Silicon Valley’ e-book into Korean and distribute it free of charge to raise awareness of ML Ops among domestic AI companies and related industries and to expand the relevant ecosystem.

Subtitle ‘Practical ML Ops Guide for Building Machine Learning Services’.

Global ML Ops platform company Balohai, Zigopt and Tecton were involved in the construction of ‘Silicon Valley’s ML Ops’. Together with Super BAI, Balohi and Tecton are part of the AI ​​Infrastructure Alliance, a consortium of global AI companies. This e-book production and Korean translation are planned as part of expanding the base of ML Ops.

The Importance of ML ML Ops in the eBook Role System of Machine Learning Projects The Difference Between Existing Software and Machine Learning పద్ధతి MLOps Workflow Measuring Method of Project ML MLOps Project Enhancement Artificial Examples of Intelligent Development and the Use of Intelligent Technology and Development Content that helps.

In particular, the ‘ML Apps Toolchain’ section contains the contents of the ‘Data Platform’ written by Superby. This section explains why a data platform is needed in a machine learning development project and the benefits that can be gained by adopting a data platform.

The ‘Roll System of Machine Learning Projects’ introduces the various roles of machine learning projects over the past four years, from startups to Fortune 500 companies through research by approximately 500 different organizations. It helps to understand machine learning projects by defining the roles and characteristics of each job in multiple disciplines including data scientists, data engineers, machine learning engineers, engineers, IT, business leaders and managers.

The ‘ML Ops Workflow’ is the appropriate workflow for ‘The Purpose of ML Ops’, ‘Machine Learning Risk Factors’, ‘Release Period’, ‘Common Language’ and when developing and operating a machine learning system. ‘Automation’. We demonstrate the construction method. In addition, it highlights the importance of creating a consistent and product-oriented product model by introducing in detail the major risk factors that arise from machine learning for production, such as ‘loss of knowledge’, ‘product failure’, and ‘regulation and ethics’. Reliable rules.

The MLOps e-book of Silicon Valley has been uploaded to the blog section on the Super BAI homepage and can be downloaded without time or expense restrictions.


Source by [ciokorea]

Re Writted By [Baji Infotech]

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