Analytics Vidhya

MAY 21, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Docker Containers Networking The concept of DevOps culture in an IT-driven organization seeks to bring synergy between the development part of the application and operations.

DevOps 356

DevOps Data Science 356

Analytics Vidhya

JULY 28, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon ML + DevOps + Data Engineer = MLOPs Origins MLOps originated. The post DeepDive into the Emerging concpet of Machine Learning Operations or MLOPs appeared first on Analytics Vidhya.

Machine Learning 337

Machine Learning DevOps Data Science ML 337

Analytics Vidhya

OCTOBER 2, 2022

This article was published as a part of the Data Science Blogathon. 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 […].

DevOps 271

DevOps Data Science Machine Learning 271

Analytics Vidhya

MARCH 21, 2022

This article was published as a part of the Data Science Blogathon. Introduction I believe all you’re familiar with the terminology DevOps for these many years, this is the complete culture and process life cycle of CI/CD.

Machine Learning 306

Machine Learning DevOps Data Science 306

AWS Machine Learning Blog

FEBRUARY 21, 2025

Rockets legacy data science environment challenges Rockets previous data science solution was built around Apache Spark and combined the use of a legacy version of the Hadoop environment and vendor-provided Data Science Experience development tools.

Data Science 71

Data Science Data Scientist Data Ingestion DevOps 71

IBM Journey to AI blog

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. How MLOps will be used within the organization.

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

Analytics Vidhya

FEBRUARY 2, 2022

This article was published as a part of the Data Science Blogathon.

DevOps 271

DevOps Software Development Machine Learning Deep Learning 271

Analytics Vidhya

MARCH 2, 2023

And also Python is a flexible language that can be applied in various domains, including scientific programming, DevOps, automation, and web development. Introduction Setting up an environment is the first step in Python development, and it’s crucial because package management can be challenging with Python.

Python 399

Python DevOps Automation Data Science 399

IBM Journey to AI blog

AUGUST 12, 2024

Consequently, AIOps is designed to harness data and insight generation capabilities to help organizations manage increasingly complex IT stacks. Here, we’ll discuss the key differences between AIOps and MLOps and how they each help teams and businesses address different IT and data science challenges.

Big Data 266

Big Data DevOps Automation Machine Learning 266

O'Reilly Media

OCTOBER 19, 2021

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments. Data Science Layers.

DevOps 145

DevOps Software Engineer Data Scientist ML 145

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.

DevOps 323

DevOps Software Development Automation Machine Learning 323

AWS Machine Learning Blog

JANUARY 5, 2024

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems.

Data Science 133

Data Science Data Drift DevOps Auto-complete 133

Flipboard

NOVEMBER 22, 2024

For example, in the bank marketing use case, the management account would be responsible for setting up the organizational structure for the bank’s data and analytics teams, provisioning separate accounts for data governance, data lakes, and data science teams, and maintaining compliance with relevant financial regulations.

ML 132

ML Data Science Metadata DevOps 132

databricks

SEPTEMBER 11, 2024

Personal Access Tokens (PATs) are a convenient way to access services like Azure Databricks or Azure DevOps without logging in with your password.

DevOps 114

DevOps ML Data Science 114

AWS Machine Learning Blog

JANUARY 23, 2025

You can use this solution to promote consistency of the analytical environments for data science teams across your enterprise. About the Authors Muni Annachi , a Senior DevOps Consultant at AWS, boasts over a decade of expertise in architecting and implementing software systems and cloud platforms.

Automation 106

Automation DevOps Machine Learning ML 106

Analytics Vidhya

NOVEMBER 1, 2022

This article was published as a part of the Data Science Blogathon. Introduction Learning its tools is one way to start having a hands-on understanding of MLOps. Understanding the tools makes the concept more practical and easy to grasp. MLOps finds its importance in place of model deployment.

Data Science 386

Data Science DevOps Machine Learning 386

Analytics Vidhya

DECEMBER 11, 2022

This article was published as a part of the Data Science Blogathon. 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.

Machine Learning 360

Machine Learning Data Scientist Data Science ML 360

Marktechpost

DECEMBER 18, 2024

DataRobot DataRobot, founded in 2012, is an AI-powered data science platform designed for building and deploying machine learning models. Nonetheless, Azure DevOps remains a robust choice for enterprises seeking a scalable and efficient development environment.

Software Development 103

Software Development AI Tools DevOps Machine Learning 103

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. My main goal as a DevOps Cloud Engineer is to achieve four objectives. What are they?

ML 116

ML DevOps Software Development Machine Learning 116

ODSC - Open Data Science

APRIL 12, 2023

In the weeks since we announced our first group of partners for ODSC East 2023 , we’ve added even more industry-leading organizations and startups helping to shape the future of AI and data science for enterprise. It currently offers services in a wide range of industries, from life sciences to wholesale distribution.

Data Science 97

Data Science Deep Learning DevOps Software Development 97

Analytics Vidhya

MAY 21, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Docker Containers Networking The concept of DevOps culture in an IT-driven organization seeks to bring synergy between the development part of the application and operations.

DevOps 143

DevOps Data Science 143

ODSC - Open Data Science

APRIL 17, 2023

DevSecOps includes all the characteristics of DevOps, such as faster deployment, automated pipelines for build and deployment, extensive testing, etc., Ltd, 2020), p:112 Conclusion In conclusion, DevSecOps plays a crucial role in ensuring data privacy and security in data science projects.

Data Science 97

Data Science DevOps Deep Learning Automation 97

Analytics Vidhya

SEPTEMBER 6, 2021

This article was published as a part of the Data Science Blogathon Introduction Building, running, browsing, moving containers and images using the Docker CLI is as easy as shelling peas, but have you ever wondered how the internals that power the Docker interface actually work?

Data Science 312

Data Science DevOps 312

Unite.AI

JUNE 19, 2024

MLOps, or Machine Learning Operations, is a multidisciplinary field that combines the principles of ML, software engineering, and DevOps practices to streamline the deployment, monitoring, and maintenance of ML models in production environments. ML Operations : Deploy and maintain ML models using established DevOps practices.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

Analytics Vidhya

APRIL 2, 2022

This article was published as a part of the Data Science Blogathon. Introduction MLOps, as a new area, is quickly gaining traction among Data Scientists, Machine Learning Engineers, and AI enthusiasts. MLOps are required for anything to reach production.

Machine Learning 269

Machine Learning Data Scientist Data Science DevOps 269

Pickl AI

APRIL 1, 2025

Cloud computing and data science are interconnected, making data-related cloud skills highly valuable. Understanding the Role of a Cloud Engineer Cloud computing has changed how businesses store and access data. Understand DevOps and CI/CD Cloud Engineers often work closely with DevOps teams to ensure smooth deployments.

DevOps 52

DevOps Data Science Automation Big Data 52

IBM Journey to AI blog

JUNE 8, 2023

He then selected Krista’s AI-powered intelligent automation platform to optimize Zimperium’s project management suite, messaging solutions, development and operations (DevOps). Zimperium saw significant cost savings and increased efficiency as it helped protect its clients against both known and unknown cybersecurity threats.

DevOps 214

DevOps Automation Machine Learning NLP 214

IBM Journey to AI blog

SEPTEMBER 20, 2023

Platforms like the Red Hat OpenShift Data Science (RHODS) and the recently announced Red Hat OpenShift AI provide tools to rapidly develop and deploy production-ready AI models in distributed cloud and edge environments. The software stack included the Red Hat OpenShift Container Platform and Red Hat OpenShift Data Science.

Large Language Models 238

Large Language Models DevOps Data Science AI Modeling 238

Pickl AI

APRIL 17, 2023

How can a DevOps team take advantage of Artificial Intelligence (AI)? DevOps is mainly the practice of combining different teams including development and operations teams to make improvements in the software delivery processes. So now, how can a DevOps team take advantage of Artificial Intelligence (AI)?

DevOps 52

DevOps Artificial Intelligence Artificial Intelligence Machine Learning 52

SAS Software

FEBRUARY 3, 2023

Between Devops, DataOps, MLOps, and ModelOps, there are different Ops based on different environments. Learning about DevOps DevOps or Developer Operations refers to applying agile [.] Ops’ generally is the shortened version of Operations. Check out some of the different Ops in our current technological world.

DevOps 109

DevOps Data Science 109

Marktechpost

JULY 5, 2024

Programming for Data Science with Python This course series teaches essential programming skills for data analysis, including SQL fundamentals for querying databases and Unix shell basics. Students also learn Python programming, from fundamentals to data manipulation with NumPy and Pandas, along with version control using Git.

Data Science 60

Data Science Machine Learning Data Analysis Software Engineer 60

Analytics Vidhya

OCTOBER 22, 2022

This article was published as a part of the Data Science Blogathon. Introduction In this article, we shall be learning how MLOps add value to an organization. So, let us […].

Data Science 223

Data Science DevOps Machine Learning 223

ODSC - Open Data Science

DECEMBER 1, 2023

Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels! You can also get data science training on-demand wherever you are with our Ai+ Training platform.

Data Science 52

Data Science DevOps Machine Learning Large Language Models 52

AWS Machine Learning Blog

FEBRUARY 27, 2024

Axfood has a structure with multiple decentralized data science teams with different areas of responsibility. Together with a central data platform team, the data science teams bring innovation and digital transformation through AI and ML solutions to the organization.

Machine Learning 135

Machine Learning DevOps Data Scientist Data Quality 135

The MLOps Blog

JANUARY 23, 2023

Lived through the DevOps revolution. If you’d like a TLDR, here it is: MLOps is an extension of DevOps. Not a fork: – The MLOps team should consist of a DevOps engineer, a backend software engineer, a data scientist, + regular software folks. Model monitoring tools will merge with the DevOps monitoring stack.

DevOps 59

DevOps Metadata Software Engineer Data Scientist 59

ODSC - Open Data Science

JANUARY 31, 2023

Getting insight into your system allows you to detect and resolve issues quickly — and it’s an essential part of DevOps best practices. Proactively monitoring systems and gathering data allows AI to provide insights that enable organizations to predict risks and prevent problems from occurring.

DevOps 105

DevOps Machine Learning Data Science Automation 105

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. My main goal as a DevOps Cloud Engineer is to achieve four objectives. What are they?

ML 111

ML DevOps Software Development Machine Learning 111