Unite.AI

JUNE 19, 2024

Operations ML Model Deployment : Implementing and deploying ML models into production environments. CI/CD Pipelines : Setting up continuous integration and delivery pipelines to automate model updates and deployments. ML Operations : Deploy and maintain ML models using established DevOps practices.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. JuMa is now available to all data scientists, ML engineers, and data analysts at BMW Group.

ML 154

ML DevOps Data Scientist ML Engineer 154

Pickl AI

JANUARY 30, 2023

Data Automation: Automate data processing pipelines and workflows using Python scripting and libraries such as PyAutoGUI and Task Scheduler. A Software Developer Uses Python: Backend Development : Python finds applications in developing server-side applications and APIs. How to Make a Career in Python?

Python 97

Python DevOps Machine Learning Data Science 97

Pickl AI

APRIL 19, 2023

Different industries from education, healthcare to marketing, retail and ecommerce require Machine Learning Engineers. Job market will experience a rise of 13% by 2026 for ML Engineers Why is Machine Learning Important? Accordingly, an entry-level ML engineer will earn around 5.1 Consequently.

Machine Learning 52

Machine Learning ML Engineer Data Scientist ML 52

The MLOps Blog

JUNE 13, 2024

When I first started working with AI, I was surprised at how complex and unstructured the development process was. Where traditional software development follows a widely agreed-upon streamlined process for developing and deploying, ML development is quite different. But getting there is a real challenge.

ML 59

ML Data Scientist Automation Software Development 59

Chatbots Life

MAY 16, 2023

10CLOUDS Year Founded : 2009 HQ : Warsaw, Poland Team Size : 51–200 employees Clients : TrustStamp (Identity verification), Emergent Tech (G-Coin), AlephZero (Blockchain), Tapeke (BitCoin Software Development), Tagasauris (Crowdsourcing Software Development), CallerSmart.

Generative AI 98

Generative AI Chatbots Conversational AI Software Development 98

AWS Machine Learning Blog

JANUARY 17, 2023

In Studio, you can load data, adjust ML models, move in between steps to adjust experiments, compare results, and deploy ML models for inference. The AWS Cloud Development Kit (AWS CDK) is an open-source software development framework to create AWS CloudFormation stacks through automatic CloudFormation template generation.

Software Engineer 92

Software Engineer ML Engineer ML Machine Learning 92

AWS Machine Learning Blog

JULY 25, 2024

By implementing features such as proactive health monitoring and automated recovery mechanisms, organizations can create a fault-tolerant environment capable of handling hardware failures or other issues without compromising the integrity of the training process. Ziwen Ning is a software development engineer at AWS.

Auto-complete 113

Auto-complete Software Development ML ML Engineer 113

Heartbeat

FEBRUARY 1, 2023

Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. In this article, we’ll learn everything there is to know about these operations and how ML engineers go about performing them. They may also be involved in the deployment process’s automation.

DevOps 96

DevOps Machine Learning Data Scientist Software Engineer 96

AWS Machine Learning Blog

DECEMBER 13, 2023

To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle.

ML 124

ML Automation Metadata Software Development 124

AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. This post is co-written with Jayadeep Pabbisetty, Sr.

ML 123

ML Machine Learning ETL Data Scientist 123

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

Data Scientist 112

Data Scientist ML Data Science Automation 112

AWS Machine Learning Blog

OCTOBER 2, 2023

An MLOps pipeline allows to automate the full ML lifecycle from data labeling to model training and deployment. Implementing an MLOps pipeline at the edge introduces additional complexities that make the automation, integration, and maintenance processes more challenging due to the increased operational overhead involved.

DevOps 116

DevOps Automation ML Computer Vision 116

Viso.ai

MARCH 29, 2024

MLflow is an open-source platform designed to manage the entire machine learning lifecycle, making it easier for ML Engineers, Data Scientists, Software Developers, and everyone involved in the process. Many machine learning projects fail to deliver practical results due to difficulties in automation and deployment.

Machine Learning 52

Machine Learning ML Automation Data Scientist 52

AWS Machine Learning Blog

MAY 15, 2024

Here, Amazon SageMaker Ground Truth allowed ML engineers to easily build the human-in-the-loop workflow (step v). Christopher de Beer is a senior software development engineer at Amazon located in Edinburgh, UK. With a background in visual design.

Generative AI 126

Generative AI AI AI Machine Learning 126

The MLOps Blog

JANUARY 23, 2023

Just so you know where I am coming from: I have a heavy software development background (15+ years in software). Came to ML from software. Founded two successful software services companies. Founded neptune.ai , a modular MLOps component for ML metadata store , aka “experiment tracker + model registry”.

DevOps 59

DevOps Metadata Software Engineer Data Scientist 59

Flipboard

MARCH 7, 2023

The main benefits of this approach are a high level of version control and reproducibility of an ML runtime environment and immediate availability of library packages because they’re installed in the image. You can implement comprehensive tests, governance, security guardrails, and CI/CD automation to produce custom app images.

Python 123

Python Data Scientist Data Science Automation 123

AWS Machine Learning Blog

MARCH 9, 2023

As machine learning (ML) models have improved, data scientists, ML engineers and researchers have shifted more of their attention to defining and bettering data quality. This has led to the emergence of a data-centric approach to ML and various techniques to improve model performance by focusing on data requirements.

ML Engineer 89

ML Engineer Convolutional Neural Networks Data Scientist Machine Learning 89

AWS Machine Learning Blog

AUGUST 22, 2024

Data scientists, ML engineers, IT staff, and DevOps teams must work together to operationalize models from research to deployment and maintenance. With SageMaker Pipelines, you get the benefits of an automated workflow that can be configured to run on a schedule based on the requirements for retraining the model.

Generative AI 119

Generative AI Metadata Python ML 119

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.

DevOps 140

DevOps Software Engineer Data Scientist ML 140

AWS Machine Learning Blog

AUGUST 20, 2024

Amazon SageMaker Ground Truth significantly reduces the cost and time required for labeling data by integrating human annotators with machine learning to automate the labeling process. He works to help AWS customers leverage machine learning applications, including prior work on ML-based fraud detection with Amazon Fraud Detector.

Software Engineer 110

Software Engineer ML Machine Learning Metadata 110

AWS Machine Learning Blog

NOVEMBER 14, 2024

It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices. Furthermore, sharing model resources directly across multiple accounts helps improve ML model approval, deployment, and auditing. Madhubalasri B.

ML 89

ML Auto-complete Auto-classification Machine Learning 89

The MLOps Blog

MARCH 15, 2023

Automation : Automating as many tasks to reduce human error and increase efficiency. Collaboration : Ensuring that all teams involved in the project, including data scientists, engineers, and operations teams, are working together effectively. Git is a distributed version control system for software development.

ETL 52

ETL Data Drift Machine Learning ML 52

The MLOps Blog

JULY 18, 2023

It’s an automated chief of staff that automates conversational tasks. We are aiming to automate that functionality so that every worker in an organization can have access to that help, just like a CEO or someone else in the company would. Jason: Hi Sabine, how’s it going? Jason, you are the co-founder and CTO of Xembly.

Conversational AI 52

Conversational AI Natural Language Processing AI AI 52

AWS Machine Learning Blog

APRIL 29, 2024

Metaflow overview Metaflow was originally developed at Netflix to enable data scientists and ML engineers to build ML/AI systems quickly and deploy them on production-grade infrastructure. How Metaflow integrates with Trainium From a Metaflow developer perspective, using Trainium is similar to other accelerators.

ML 123

ML Python Data Scientist Deep Learning 123

AWS Machine Learning Blog

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. Lastly, we connect these together with an example LLM workload to describe an approach towards architecting with defense-in-depth security across trust boundaries.

Generative AI 139

Generative AI LLM ML AI 139

The MLOps Blog

MARCH 21, 2023

As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale. In this comprehensive guide, we’ll explore everything you need to know about machine learning platforms, including: Components that make up an ML platform.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

AWS Machine Learning Blog

JUNE 24, 2024

Krikey AI used SageMaker Ground Truth to expedite the development and implementation of their text-to-animation model. Amanda Lester is a Senior Go-to-Market Specialist at AWS, helping to put artificial intelligence and machine learning in the hands of every developer and ML engineer.

AI Development 110

AI Development AI Developer Generative AI AI 110