AWS Machine Learning Blog

JUNE 18, 2024

This post presents a solution that uses a generative artificial intelligence (AI) to standardize air quality data from low-cost sensors in Africa, specifically addressing the air quality data integration problem of low-cost sensors. Qiong (Jo) Zhang , PhD, is a Senior Partner Solutions Architect at AWS, specializing in AI/ML.

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AWS Machine Learning Blog

DECEMBER 18, 2024

AIs transformative impact extends throughout the modern business landscape, with telecommunications emerging as a key area of innovation. Fastweb , one of Italys leading telecommunications operators, recognized the immense potential of AI technologies early on and began investing in this area in 2019.

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Flipboard

NOVEMBER 24, 2023

Data scientists and ML engineers require capable tooling and sufficient compute for their work. To pave the way for the growth of AI, BMW Group needed to make a leap regarding scalability and elasticity while reducing operational overhead, software licensing, and hardware management.

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Towards AI

FEBRUARY 17, 2025

Originally published on Towards AI. RAFT vs Fine-Tuning Image created by author As the use of large language models (LLMs) grows within businesses, to automate tasks, analyse data, and engage with customers; adapting these models to specific needs (e.g., Security: Secure sensitive data with access control (role-based) and metadata.

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Flipboard

MAY 21, 2025

The University of British Columbia (UBC) Cloud Innovation Centre (CIC) has become a hub for innovation by prototyping generative AI applications in collaboration with public sector sponsors. Importance of rapid prototyping in AI development Rapid prototyping is critical in AI development.

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AWS Machine Learning Blog

AUGUST 21, 2024

In the following sections, we provide a detailed, step-by-step guide on implementing these new capabilities, covering everything from data preparation to job submission and output analysis. This use case serves to illustrate the broader potential of the feature for handling diverse data processing tasks.

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Dataconomy

MAY 14, 2025

Consumer behavior is on the brink of a dramatic shift thanks to Agentic AI autonomous intelligent agents that act on behalf of users. Unlike traditional chatbots or static assistants, these AI agents can proactively navigate apps and websites, make decisions, and execute tasks end-to-end.

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IBM Journey to AI blog

AUGUST 12, 2024

AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps). However, they differ fundamentally in their purpose and level of specialization in AI and ML environments.

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IBM Journey to AI blog

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

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The MLOps Blog

JUNE 27, 2023

See also Thoughtworks’s guide to Evaluating MLOps Platforms End-to-end MLOps platforms End-to-end MLOps platforms provide a unified ecosystem that streamlines the entire ML workflow, from data preparation and model development to deployment and monitoring. Might be useful Unlike manual, homegrown, or open-source solutions, neptune.ai

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AWS Machine Learning Blog

OCTOBER 18, 2023

Purina used artificial intelligence (AI) and machine learning (ML) to automate animal breed detection at scale. The solution focuses on the fundamental principles of developing an AI/ML application workflow of data preparation, model training, model evaluation, and model monitoring.

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Ocean Protocol

NOVEMBER 28, 2024

Yunus focused on building a robust data pipeline, merging historical and current-season data to create a comprehensive dataset. Yunus secured third place by delivering a flexible, well-documented solution that bridged data science and Formula 1 strategy. Follow Ocean on Twitter or Telegram to stay up to date.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. Further expanding the capabilities of AI in marketing, Zeta Global has developed AI Lookalikes.

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DataRobot

SEPTEMBER 14, 2021

Time and time again, we hear about the need for AI to support cross-functional teams and users. To provide the ability to integrate diverse data sources. To offer the flexibility to deploy AI solutions anywhere. The DataRobot AI Cloud Platform is the culmination of nearly a decade of pioneering AI innovation, representing 1.5

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ODSC - Open Data Science

OCTOBER 7, 2024

In today’s landscape, AI is becoming a major focus in developing and deploying machine learning models. It isn’t just about writing code or creating algorithms — it requires robust pipelines that handle data, model training, deployment, and maintenance. As datasets grow, scalable data ingestion and storage become critical.

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AWS Machine Learning Blog

SEPTEMBER 18, 2023

Ray AI Runtime (AIR) reduces friction of going from development to production. Amazon SageMaker Pipelines allows orchestrating the end-to-end ML lifecycle from data preparation and training to model deployment as automated workflows. We set up an end-to-end Ray-based ML workflow, orchestrated using SageMaker Pipelines.

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AWS Machine Learning Blog

MARCH 1, 2023

Continuous ML model retraining is one method to overcome this challenge by relearning from the most recent data. This requires not only well-designed features and ML architecture, but also data preparation and ML pipelines that can automate the retraining process.

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ODSC - Open Data Science

MAY 10, 2023

Unfortunately, even the data science industry — which should recognize tabular data’s true value — often underestimates its relevance in AI. Many mistakenly equate tabular data with business intelligence rather than AI, leading to a dismissive attitude toward its sophistication.

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Flipboard

AUGUST 17, 2023

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, ML, and application development. Above all, this solution offers you a native Spark way to implement an end-to-end data pipeline from Amazon Redshift to SageMaker.

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Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. They are crucial in ensuring data is readily available for analysis and reporting.

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DataRobot Blog

OCTOBER 3, 2017

Standard Chartered Bank’s Global Head of Technology, Santhosh Mahendiran , discussed the democratization of data across 3,500+ business users in 68 countries. We look at data as an asset, regardless of whether the use case is AML/fraud or new revenue. 3) Data professionals come in all shapes and forms. DataRobot Data Prep.

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Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

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AWS Machine Learning Blog

MARCH 8, 2023

In order to train a model using data stored outside of the three supported storage services, the data first needs to be ingested into one of these services (typically Amazon S3). This requires building a data pipeline (using tools such as Amazon SageMaker Data Wrangler ) to move data into Amazon S3.

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DataRobot Blog

APRIL 1, 2018

Today’s data management and analytics products have infused artificial intelligence (AI) and machine learning (ML) algorithms into their core capabilities. These modern tools will auto-profile the data, detect joins and overlaps, and offer recommendations. 2) Line of business is taking a more active role in data projects.

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phData

AUGUST 2, 2024

Efficient data transformation and processing are crucial for data analytics and generating insights. Snowflake AI Data Cloud is one of the most powerful platforms, including storage services supporting complex data. Integrating Snowflake with dbt adds another layer of automation and control to the data pipeline.

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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.

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Pickl AI

OCTOBER 17, 2024

Summary: This article explores the significance of ETL Data in Data Management. It highlights key components of the ETL process, best practices for efficiency, and future trends like AI integration and real-time processing, ensuring organisations can leverage their data effectively for strategic decision-making.

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Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Data preparation, train and tune, deploy and monitor. Hope you can all hear me well.

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Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Data preparation, train and tune, deploy and monitor. Hope you can all hear me well.

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Pickl AI

FEBRUARY 8, 2023

Data Scientists and Data Analysts have been using ChatGPT for Data Science to generate codes and answers rapidly. Data Manipulation The process through which you can change the data according to your project requirement for further data analysis is known as Data Manipulation.

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Iguazio

FEBRUARY 8, 2024

Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. LLM examples include GPT, BERT, and similar advanced AI systems. They are characterized by their enormous size, complexity, and the vast amount of data they process.

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phData

FEBRUARY 24, 2023

Alteryx provides organizations with an opportunity to automate access to data, analytics , data science, and process automation all in one, end-to-end platform. Its capabilities can be split into the following topics: automating inputs & outputs, data preparation, data enrichment, and data science.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). And finally, some activities, such as those involved with the latest advances in artificial intelligence (AI), are simply not practically possible, without hardware acceleration.

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Pickl AI

APRIL 9, 2025

Airflow is particularly useful for organizations that require flexibility and scalability in their data pipelines. It simplifies the process of data preparation for analytics by automatically discovering and categorizing data. It allows users to define complex workflows as code and provides scheduling capabilities.

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Pickl AI

JULY 24, 2024

Future Trends and Innovations The evolving landscape of data, characterised by exponential growth, increasing complexity, and the imperative for real-time insights, is driving rapid advancements in data quality practices. AI and Machine Learning These are emerging as powerful tools for enhancing data quality.

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Pickl AI

OCTOBER 10, 2024

Informatica Informatica is a powerful enterprise-grade data management platform offering a range of tools for data integration, transformation, and governance. It supports batch and real-time data processing, making it a preferred choice for large enterprises with complex data workflows.

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phData

SEPTEMBER 25, 2024

In this blog, we will provide a comprehensive overview of ETL considerations, introduce key tools such as Fivetran, Salesforce, and Snowflake AI Data Cloud , and demonstrate how to set up a pipeline and ingest data between Salesforce and Snowflake using Fivetran. What is Fivetran?

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