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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. The same survey shows that putting a model from a research environment to production — where it eventually starts adding business value — takes between 8 to 90 days on average. Data validation. Data preparation.

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The Good and the Bad of Python Programming Language

Altexsoft

web development, data analysis. Source: Python Developers Survey 2020 Results. This distinguishes Python from domain-specific languages like HTML and CSS limited to web design or SQL created for accessing data in relational database management systems. 2021 Stackoverflow survey of the most popular technologies.

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Technology Trends for 2023

O'Reilly Media - Ideas

JavaScript shows up at, or near, the top on most programming language surveys, such as RedMonk’s rankings (usually in a virtual tie with Java and Python). Data Data is another very broad category, encompassing everything from traditional business analytics to artificial intelligence. year-over-year decline.

Trends 134
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The Good and the Bad of Docker Containers

Altexsoft

delivering microservice-based and cloud-native applications; standardized continuous integration and delivery ( CI/CD ) processes for applications; isolation of multiple parallel applications on a host system; faster application development; software migration; and. Source: Stack Overflow Developer Survey 2022.

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Technology Trends for 2022

O'Reilly Media - Ideas

A quick look at bigram usage (word pairs) doesn’t really distinguish between “data science,” “data engineering,” “data analysis,” and other terms; the most common word pair with “data” is “data governance,” followed by “data science.” That’s certainly true of our audience as a whole.

Trends 110
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What are model governance and model operations?

O'Reilly Media - Ideas

Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Other noteworthy items include: Tools for continuous integration and continuous testing of models. A model is not “correct” if it returns a valid value—it has to meet an accuracy bar.

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AutoML: How to Automate Machine Learning With Google Vertex AI, Amazon SageMaker, H20.ai, and Other Providers

Altexsoft

The rest is done by data engineers, data scientists , machine learning engineers , and other high-trained (and high-paid) specialists. Also called DevOps for machine learning, MLOps is a mix of philosophy and practices that facilitates mutual understanding between a data science team and operations specialists.