AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. According to a McKinsey study , across the financial services industry (FSI), generative AI is projected to deliver over $400 billion (5%) of industry revenue in productivity benefits.

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Towards AI

MARCH 3, 2024

Ah, the wild world of data science and machine learning, where algorithms roam free, and models hold the keys to unlocking the mysteries of the universe. But in this jungle of ones and zeros, there lies a crucial tool — MLOps, the superhero of streamlined development and deployment. But wait, there’s more!

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Towards AI

JANUARY 27, 2024

Unlocking the Power of Compose for Seamless Machine Learning WorkflowsPhoto by Larisa Birta on Unsplash In the ever-evolving landscape of machine learning experimentation and application development, navigating the coordination of diverse system components poses a significant logistical challenge.

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DrivenData Labs

MAY 18, 2023

My research focuses on differential privacy and explainable machine learning but extends to other areas where applying formal models brings new ideas to the table. What is a recent project you’ve worked on that you’re excited about or other interesting work you can share? I'm currently getting set up on a Framework 13.

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Data Science Dojo

SEPTEMBER 22, 2023

As technology continues to advance at an unprecedented rate, AI is rapidly transforming the way we live and work. Key strategies for people management in AI: As AI continues to transform the workplace, the role of people management is becoming increasingly important. Here are some key strategies for people management in AI: 1.

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IBM Journey to AI blog

APRIL 9, 2024

In a continuous design thinking process, teams from IBM Consulting and the club collaborate to improve the fan experience year after year. In a continuous design thinking process, teams from IBM Consulting and the club collaborate to improve the fan experience year after year. Lastly, watsonx.data pulls from live feeds.

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The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors.

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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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phData

MAY 28, 2024

The Snowflake Data Cloud continues to push the boundaries with innovative tools designed to enhance data processing and analysis. Snowflake Cortex is a suite of pre-built machine learning models and AI capabilities designed to accelerate the deployment of AI-driven solutions within the Snowflake ecosystem.

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AWS Machine Learning Blog

APRIL 29, 2024

Arcee’s innovative continual pre-training (CPT) and model merging techniques have brought a significant leap forward in the efficient training of LLMs, with particularly strong evaluations in the medical, legal, and financial verticals. In this post, we show you how efficient we make our continual pre-training by using Trainium chips.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. Philips is a health technology company focused on improving people’s lives through meaningful innovation.

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AWS Machine Learning Blog

DECEMBER 4, 2023

We capitalized on the powerful tools provided by AWS to tackle this challenge and effectively navigate the complex field of machine learning (ML) and predictive analytics. This is a guest post co-authored by Nafi Ahmet Turgut, Hasan Burak Yel, and Damla Şentürk from Getir. SageMaker is a fully managed ML service.

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IBM Journey to AI blog

JUNE 8, 2023

However, for many enterprises, the barrier to entry for integrating trustworthy, scalable and transparent AI remains high. In fact, 80% of enterprise AI projects never make it out of the lab. With machine learning-based protection through a single platform, Zimperium offers customers mobile threat defense and in-app protection.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

By using the Framework, you will learn operational and architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable workloads in the cloud. This custom lens integrates best practices and guidance to effectively navigate and overcome common challenges in the management of IDP workloads.

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AWS Machine Learning Blog

MARCH 13, 2024

JumpStart is the machine learning (ML) hub of SageMaker that provides access to foundation models in addition to built-in algorithms and end-to-end solution templates to help you quickly get started with ML. The Gemma family consists of two sizes: a 7 billion parameter model and a 2 billion parameter model.

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IBM Journey to AI blog

NOVEMBER 9, 2023

In 2021, Liquid Prep became an open-source software project hosted by the Linux Foundation. In 2021, Liquid Prep became an open-source software project hosted by the Linux Foundation. Challenges and scalability As Liquid Prep continued to evolve, the need for a single sensor to measure plants in more than one location became evident.

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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. The SageMaker Model Registry centralizes model tracking, simplifying model deployment.

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Heartbeat

JUNE 5, 2023

In recent years, machine learning has exploded in popularity because of its wide range of potential uses in fields including healthcare, finance, eCommerce, and the arts. However, managing machine learning projects can be challenging, especially as the size and complexity of the data and models increase.

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DataRobot Blog

JULY 21, 2022

Download the Machine Learning Project Checklist. Planning Machine Learning Projects. Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. More organizations are investing in machine learning than ever before.

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AWS Machine Learning Blog

MARCH 15, 2024

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. To address this issue, federated learning (FL) is a decentralized and collaborative ML training technique that offers data privacy while maintaining accuracy and fidelity.

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The MLOps Blog

JANUARY 26, 2024

TL;DR Feedback integration is crucial for ML models to meet user needs. Technical projects must be aligned with business objectives. In this article, I will outline the learnings and challenges I faced while on the ML platform team at Mailchimp, building infrastructure and setting up the environment for development and testing.

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AWS Machine Learning Blog

MAY 14, 2024

An important aspect of developing effective generative AI application is Reinforcement Learning from Human Feedback (RLHF). An important aspect of developing effective generative AI application is Reinforcement Learning from Human Feedback (RLHF).

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The MLOps Blog

MAY 9, 2023

They run scripts manually to preprocess their training data, rerun the deployment scripts, manually tune their models, and spend their working hours keeping previously developed models up to date. Building end-to-end machine learning pipelines lets ML engineers build once, rerun, and reuse many times.

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Heartbeat

JULY 31, 2023

Image by Author from Comet Machine learning has rapidly become an essential part of many industries, including finance, healthcare, and retail. However, training and deploying large-scale machine learning models can be a complex and time-consuming process. This is where Comet comes in.

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AWS Machine Learning Blog

JUNE 14, 2023

Amazon SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. Every organization has its own set of standards and practices that provide security and governance for their AWS environment.

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AWS Machine Learning Blog

MAY 17, 2024

You can try out this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models so you can quickly get started with ML. In this post, we walk through how to discover and deploy the Mixtral-8x22B model. making the model available for exploring, testing, and deploying.

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AWS Machine Learning Blog

MARCH 1, 2024

Machine learning (ML) technologies continually improve and power the contact center customer experience by providing solutions for capabilities like self-service bots, live call analytics, and post-call analytics.

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AWS Machine Learning Blog

MAY 16, 2024

To enhance the shopping experience of LotteON’s customers, the recommendation service development team is continuously improving the recommendation service to provide customers with the products they are looking for or may be interested in at the right time.

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Heartbeat

FEBRUARY 28, 2024

Experimentation is the lifeblood of machine learning. This article will explore how two powerful tools, Comet and Gradio, simplify and enhance your machine learning journey. This article will explore how two powerful tools, Comet and Gradio, simplify and enhance your machine learning journey.

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AWS Machine Learning Blog

JULY 19, 2023

However, when solving a business problem through a machine learning (ML) model, as customers iterate on the problem, they create multiple versions of the model and they need to operationalize and govern multiple model versions. The following figure illustrates how a SageMaker model card integrates with the model registry.

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AWS Machine Learning Blog

MAY 17, 2024

Like all AI, generative AI works by using machine learning models—very large models that are pretrained on vast amounts of data called foundation models (FMs). FMs and LLMs, even though they’re pre-trained, can continue to learn from data inputs or prompts during inference.

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The MLOps Blog

MARCH 12, 2024

TL;DR LLMOps involves managing the entire lifecycle of Large Language Models (LLMs), including data and prompt management, model fine-tuning and evaluation, pipeline orchestration, and LLM deployment. You will learn: The unique challenges LLMOps addresses. LLMOps encompasses best practices and a diverse tooling landscape.

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IBM Journey to AI blog

DECEMBER 15, 2023

Open-source AI projects and libraries, freely available on platforms like GitHub, fuel digital innovation in industries like healthcare, finance and education. Readily available frameworks and tools empower developers by saving time and allowing them to focus on creating bespoke solutions to meet specific project requirements.

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phData

MARCH 4, 2024

In this blog, we’ll explore Snowflake’s most compelling features that support artificial intelligence and investigate the future of AI with Snowflake. This facilitates the deployment and administration of models entirely within Snowflake, eliminating the need for data transfers, silos, or governance compromises.

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AWS Machine Learning Blog

JUNE 16, 2023

In this post, we discuss how SambaSafety used AWS machine learning (ML) and continuous integration and continuous delivery (CI/CD) tools to deploy their existing data science application for batch inference. Not all drivers present the same risk profile.

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Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

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Heartbeat

OCTOBER 5, 2023

Unsurprisingly, Machine Learning (ML) has seen remarkable progress, revolutionizing industries and how we interact with technology. This is where the world of operations steps in, and while MLOps (Machine Learning Operations) has been a guiding light, a new paradigm is emerging — LLMOps (Large Language Model Operations).

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