Analytics Vidhya

JANUARY 25, 2022

Introduction In this article, we will be going through two concepts MLOps and DevOps. As you might be aware in DevOps we try to bring together […]. The post MLOps vs DevOps: Let’s Understand the Differences? We will first try to get through their basics and then we will explore the differences between them.

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Analytics Vidhya

DECEMBER 11, 2022

Introduction Machine learning (ML) has become an increasingly important tool for organizations of all sizes, providing the ability to learn and improve from data automatically. The post Streamlining Machine Learning Workflows with MLOps appeared first on Analytics Vidhya.

Machine Learning 360

Machine Learning Data Scientist Data Science ML 360

Analytics Vidhya

APRIL 2, 2022

Introduction MLOps, as a new area, is quickly gaining traction among Data Scientists, Machine Learning Engineers, and AI enthusiasts. The post Your Go-to Guide on Machine Learning Operations (MLOps) appeared first on Analytics Vidhya. MLOps are required for anything to reach production.

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Analytics Vidhya

FEBRUARY 2, 2022

Table of contents Overview Traditional Software development Life Cycle Waterfall Model Agile Model DevOps Challenges in ML models Understanding MLOps Data Engineering Machine Learning DevOps Endnotes Overview: MLOps According to research by deeplearning.ai, only 2% of the companies using Machine Learning, Deep learning have […].

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Unite.AI

FEBRUARY 6, 2025

The exponential rise of generative AI has brought new challenges for enterprises looking to deploy machine learning models at scale. Key features include model cataloging, fine-tuning, API deployment, and advanced governance tools that bridge the gap between DevOps and MLOps.

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Analytics Vidhya

MAY 30, 2022

Docker is a DevOps tool and is very popular in the DevOps and MLOPS world. This article was published as a part of the Data Science Blogathon. Introduction on Docker Docker is everywhere in the world of the software industry today. The post A Complete Guide for Deploying ML Models in Docker appeared first on Analytics Vidhya.

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ML DevOps Data Science Python 374

IBM Journey to AI blog

AUGUST 12, 2024

Instead, businesses tend to rely on advanced tools and strategies—namely artificial intelligence for IT operations (AIOps) and machine learning operations (MLOps)—to turn vast quantities of data into actionable insights that can improve IT decision-making and ultimately, the bottom line.

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Big Data DevOps Automation Machine Learning 266

IBM Journey to AI blog

NOVEMBER 13, 2023

Overview of Kubernetes Containers —lightweight units of software that package code and all its dependencies to run in any environment—form the foundation of Kubernetes and are mission-critical for modern microservices, cloud-native software and DevOps workflows.

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Analytics Vidhya

NOVEMBER 23, 2020

Introduction This article outlines the motivation behind MLOps, its relation to DevOps, The post MLOps – the Why and the What appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

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DevOps Data Science Machine Learning 394

Flipboard

FEBRUARY 24, 2025

Hrushikesh Deshmukh, Senior Consultant, Fannie Mae. Predictive monitoring is transforming enterprise operations by combining the latest technologies with strategic implementation. By preventing issues before they escalate through early detection, enhancement of reliability and better performance

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Analytics Vidhya

OCTOBER 2, 2022

Many persons have barely finished digesting the meaning of DevOps, and here come a new term, MLOps. But, those who understand the meaning of the older term DevOps are on the safe side. So, if you know what’s DevOps and you […]. This article was published as a part of the Data Science Blogathon. Introduction MLOps?

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DevOps Data Science Machine Learning 271

AWS Machine Learning Blog

JANUARY 23, 2025

The solution described in this post is geared towards machine learning (ML) engineers and platform teams who are often responsible for managing and standardizing custom environments at scale across an organization. This approach helps you achieve machine learning (ML) governance, scalability, and standardization.

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Automation DevOps Machine Learning ML 100

IBM Journey to AI blog

OCTOBER 13, 2023

By leveraging machine learning algorithms, Instana can identify patterns and trends in application behavior, anticipating issues before they manifest as problems. AI-driven root cause analysis Instana leverages artificial intelligence (AI) and machine learning algorithms to provide accurate and intelligent root cause analysis.

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O'Reilly Media

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. This approach has worked well for software development, so it is reasonable to assume that it could address struggles related to deploying machine learning in production too. The new category is often called MLOps.

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Marktechpost

NOVEMBER 23, 2024

It includes videos and hands-on labs to improve data analysis and machine learning workflows. Through hands-on labs, you learn to prompt Gemini for specific networking guidance, enhancing your Google Cloud VPC workflows. Gemini for DevOps Engineers This course teaches engineers to use Gemini to manage infrastructure.

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Towards AI

DECEMBER 26, 2024

Source: Image By Author As a Cloud Engineer, Ive recently collaborated with a number of project teams, and my primary contribution to these teams has been to do the DevOps duties required on the GCP Cloud. To learn more about me, read the following: Am I Going in the Right Direction? What are they? But how does it do?

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ML DevOps Software Development Machine Learning 116

Marktechpost

DECEMBER 18, 2024

DataRobot DataRobot, founded in 2012, is an AI-powered data science platform designed for building and deploying machine learning models. It offers powerful capabilities in natural language processing (NLP), machine learning, data analysis, and decision optimization.

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Software Development AI Tools DevOps Machine Learning 103

AWS Machine Learning Blog

MARCH 27, 2024

Although much of the focus around analysis of DevOps is on distributed and cloud technologies, the mainframe still maintains a unique and powerful position, and it can use the DORA 4 metrics to further its reputation as the engine of commerce. Check out the BMC website to learn more and set up a demo.

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AWS Machine Learning Blog

FEBRUARY 27, 2024

In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker. This is a guest post written by Axfood AB.

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AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. Machine learning operations (MLOps) applies DevOps principles to ML systems.

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Machine Learning ML Engineer DevOps ML 121

Unite.AI

JUNE 19, 2024

In world of Artificial Intelligence (AI) and Machine Learning (ML), a new professionals has emerged, bridging the gap between cutting-edge algorithms and real-world deployment. Machine Learning Frameworks : Experience with TensorFlow , PyTorch , scikit-learn , or Keras.

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Software Engineer DevOps Machine Learning ML 176

AWS Machine Learning Blog

DECEMBER 12, 2023

This new workforce requires rapid reskilling and understanding of disruptive services such as artificial intelligence (AI) and machine learning (ML) to drive meaningful outcomes. Why is machine learning important to Vodafone? In this post, we share how Vodafone is advancing its ML skills using AWS DeepRacer and Accenture.

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Machine Learning ML DevOps Software Engineer 120

Flipboard

MARCH 21, 2025

AI for IT operations (AIOps) is the application of AI and machine learning (ML) technologies to automate and enhance IT operations. By providing developers expert guidance grounded in AWS best practices, this AI assistant enables DevOps teams to review and optimize cloud architecture across of AWS accounts.

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Automation Large Language Models Generative AI DevOps 163

Marktechpost

FEBRUARY 27, 2024

Managing and serving features to real-time models in machine learning poses a significant challenge for ML platform teams. Existing options often involve intricate dataset joining logic and lack the necessary abstraction to decouple machine learning from data infrastructure.

Machine Learning 103

Machine Learning DevOps Data Scientist ML 103

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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Data Science DevOps Machine Learning Data Scientist 170

Becoming Human

MAY 11, 2023

Machine learning operations, or MLOps, are the set of practices and tools that aim to streamline and automate the machine learning lifecycle. MLOps projects are projects that focus on implementing machine learning operations best practices into a company’s existing software development and deployment process.

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Machine Learning DevOps Software Development Data Scientist 78

Unite.AI

SEPTEMBER 30, 2024

Machine learning models analyze historical data to detect high-risk areas, prioritize test cases, and optimize test coverage. Intelligent Testing: Machine learning analyzes past data to identify high-risk areas and helps prioritize which test cases need attention first. AI-powered QA is also becoming central to DevOps.

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AWS Machine Learning Blog

FEBRUARY 28, 2025

As organizations adopt AI and machine learning (ML), theyre using these technologies to improve processes and enhance products. Automat-it specializes in helping startups and scaleups grow through hands-on cloud DevOps, MLOps and FinOps services. Outside of work, Claudiu enjoys reading, traveling, and playing chess.

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AWS Machine Learning Blog

JANUARY 13, 2025

The following diagram shows the reference architecture for various personas, including developers, support engineers, DevOps, and FinOps to connect with internal databases and the web using Amazon Q Business. You can also assume a persona such as FinOps or DevOps and get personalized recommendations or responses. Sona Rajamani is a Sr.

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DevOps Generative AI Automation Data Scientist 93

Unite.AI

OCTOBER 4, 2023

Another recent announcement was the launch of Next generation version of Amdocs Cloud Management Platform which leverages the amAIz GenAI framework for automating the entire lifecycle of IT and is built to accelerate service providers’ journey to cloud, utilizing DevOps and FinOps.

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AWS Machine Learning Blog

OCTOBER 16, 2024

Solution overview Intact aimed to develop a cost-effective and efficient call analytics platform for their contact centers by using speech-to-text and machine learning technologies. Machine learning operations (MLOps) Intact also built an automated MLOps pipeline that use Step Functions, Lambda, and Amazon S3.

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Machine Learning Data Scientist Deep Learning ML 76

IBM Journey to AI blog

JUNE 8, 2023

With machine learning-based protection through a single platform, Zimperium offers customers mobile threat defense and in-app protection. He then selected Krista’s AI-powered intelligent automation platform to optimize Zimperium’s project management suite, messaging solutions, development and operations (DevOps).

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AWS Machine Learning Blog

MARCH 30, 2023

In this post, we introduce a new interactive tool called Snapper, powered by a machine learning (ML) model that reduces the effort required of annotators. About the authors Jonathan Buck is a Software Engineer at Amazon Web Services working at the intersection of machine learning and distributed systems.

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IBM Journey to AI blog

DECEMBER 20, 2023

For instance, a DevOps team can quickly scale or extend an application’s functionality by adding new microservices without having to add a line of code or affecting other aspects of the application. Business acceleration : Harness the latest cloud technologies, such as generative AI and machine learning, to gain a competitive edge.

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DevOps Machine Learning Automation Big Data 294

IBM Journey to AI blog

SEPTEMBER 12, 2023

In today’s complex and dynamic environments, traditional manual approaches fall short in delivering the agility, accuracy and scalability demanded by site reliability engineering (SRE) and DevOps practices.

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Automation DevOps Machine Learning Explainability 206

IBM Journey to AI blog

FEBRUARY 29, 2024

A hypervisor is used to oversee microservice operations when more than one virtual machine is being used on a computer.

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Flipboard

DECEMBER 10, 2024

Technology operations (TechOps) is a broad topic that includes AIOps, SecOps, DevOps, FinOps, DataOps and so on. Sandeep Shilawat is a renowned tech innovator, thought leader and strategic advisor in U.S. federal markets. Generative AI (GenAI), armed with large language models (LLMs) and agentic AI,

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