Cloud Computing, Data Preparation and ML

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

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.

ML

ML ML AWS AI

A generative AI prototype with Amazon Bedrock transforms life sciences and the genome analysis process

Flipboard

MAY 28, 2025

This approach was use case-specific and required data preparation and manual work. About the Authors Ganesh Raam Ramadurai is a Senior Technical Program Manager at Amazon Web Services (AWS), where he leads the PACE (Prototyping and Cloud Engineering) team.

SQL

SQL AWS AI AI

Build an end-to-end MLOps pipeline using Amazon SageMaker Pipelines, GitHub, and GitHub Actions

AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. GitHub serves as a centralized location to store, version, and manage your ML code base.

AWS

AWS ML ML Data Preparation

Webinars

Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

MORE WEBINARS

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

Machine Learning

Machine Learning Machine Learning ML ML

Must-Have Skills for a Machine Learning Engineer

Pickl AI

NOVEMBER 28, 2024

Understanding Machine Learning algorithms and effective data handling are also critical for success in the field. Introduction Machine Learning ( ML ) is revolutionising industries, from healthcare and finance to retail and manufacturing. Familiarity with cloud computing tools supports scalable model deployment.

Machine Learning

Machine Learning Machine Learning ML ML

Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

MAY 15, 2023

Note : Now write some articles or blogs on the things you have learned because this thing will help you to develop soft skills as well if you want to publish some research paper on AI/ML so this writing habit will help you there for sure. It provides end-to-end pipeline components for building scalable and reliable ML production systems.

Data Science

Data Science Machine Learning Machine Learning Database

Predicting the Future of Data Science

Pickl AI

DECEMBER 4, 2024

This explosive growth is driven by the increasing volume of data generated daily, with estimates suggesting that by 2025, there will be around 181 zettabytes of data created globally. Learn to use tools like Tableau, Power BI, or Matplotlib to create compelling visual representations of data.

Data Science

Data Science Data Scientist Machine Learning Machine Learning

13 Companies Leading the Way in AI Development

ODSC - Open Data Science

OCTOBER 9, 2023

BPCS’s deep understanding of Databricks can help organizations of all sizes get the most out of the platform, with services spanning data migration, engineering, science, ML, and cloud optimization. HPCC is a high-performance computing platform that helps organizations process and analyze large amounts of data.

Machine Learning

Machine Learning Machine Learning Data Science AI

AI Models as a Service (AIMaaS): A Detailed Overview

Pickl AI

OCTOBER 3, 2024

Data Management Tools These platforms often provide robust data management features that assist in data preparation, cleaning, and augmentation, which are crucial for training effective AI models. These providers are leveraging their expertise in cloud computing and Machine Learning to deliver powerful AIMaaS offerings.

Machine Learning

Machine Learning Machine Learning AI AI

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning Blog

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

AWS

AWS ML ML AI

ML scalability

Dataconomy

APRIL 25, 2025

ML scalability is a crucial aspect of machine learning systems, particularly as data continues to grow exponentially. What is ML scalability? ML scalability refers to the capacity of machine learning systems to effectively handle larger datasets and increasing user demands.

ML

ML ML Machine Learning Machine Learning

ML orchestration

Dataconomy

APRIL 14, 2025

ML orchestration has emerged as a critical component in modern machine learning frameworks, providing a comprehensive approach to automate and streamline the various stages of the machine learning lifecycle. This article delves into the intricacies of ML orchestration, exploring its significance and key features.

ML

ML ML Machine Learning Machine Learning

Embodied AI Chess with Amazon Bedrock

AWS Machine Learning Blog

NOVEMBER 27, 2024

This approach to data preparation creates the foundation for fine-tuning a model that can play chess at a high level. Fine-tune a model With our refined dataset prepared from successful games and legal moves, we now proceed to fine-tune a model using Amazon SageMaker JumpStart.

AWS

AWS AI AI Python

How Fastweb fine-tuned the Mistral model using Amazon SageMaker HyperPod as a first step to build an Italian large language model

AWS Machine Learning Blog

DECEMBER 18, 2024

With a vision to build a large language model (LLM) trained on Italian data, Fastweb embarked on a journey to make this powerful AI capability available to third parties. He has worked on projects in different domains, including MLOps, computer vision, and NLP, involving a broad set of AWS services.

Clustering

Clustering AWS AI AI

15 Fan-Favorite Speakers & Instructors Returning for ODSC East 2025

ODSC - Open Data Science

MARCH 18, 2025

With over 30 years in techincluding key roles at Hugging Face, AWS, and as a startup CTOhe brings unparalleled expertise in cloud computing and machine learning. Before Arize, Amber was a Product Manager of AI/ML at Splunk and Head of Artificial Intelligence at Insight Data Science.

Data Science

Data Science Machine Learning Machine Learning Data Scientist

Data Science Current

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

A generative AI prototype with Amazon Bedrock transforms life sciences and the genome analysis process

Webinars

Trending Sources

Build an end-to-end MLOps pipeline using Amazon SageMaker Pipelines, GitHub, and GitHub Actions

Webinars

MLOps Landscape in 2023: Top Tools and Platforms

Must-Have Skills for a Machine Learning Engineer

Roadmap to Learn Data Science for Beginners and Freshers in 2023

Predicting the Future of Data Science

13 Companies Leading the Way in AI Development

AI Models as a Service (AIMaaS): A Detailed Overview

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

ML scalability

ML orchestration

Embodied AI Chess with Amazon Bedrock

How Fastweb fine-tuned the Mistral model using Amazon SageMaker HyperPod as a first step to build an Italian large language model

15 Fan-Favorite Speakers & Instructors Returning for ODSC East 2025

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