Dataconomy

MAY 6, 2025

This involves: Storing preprocessed data: Utilizing databases or data lakes to preserve data efficiently. Optimizing data formats: Ensuring that data is formatted for effective querying and analysis. Model training Model training is the phase where prepared data is used to develop machine learning models.

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ML ML Machine Learning Machine Learning 91

IBM Journey to AI blog

MAY 9, 2023

As a result, businesses have focused mainly on automating tasks with abundant data and high business value, leaving everything else on the table. models are trained on IBM’s curated, enterprise-focused data lake, on our custom-designed cloud-native AI supercomputer, Vela. But this is starting to change. All watsonx.ai

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AI AI Data Quality Data Lakes 139

How to Learn Machine Learning

MAY 2, 2025

Best Practices for Azure Machine Learning Projects To get the most out of Azure Machine Learning, consider these best practices: Data Management Use Azure Data Stores : Connect to various data sources including Azure Blob Storage, Azure Data Lake, and Azure SQL Database for efficient data access.

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Azure Machine Learning Machine Learning Data Science 52

IBM Journey to AI blog

AUGUST 1, 2023

Foundation models can be trained to perform tasks such as data classification, the identification of objects within images (computer vision) and natural language processing (NLP) (understanding and generating text) with a high degree of accuracy. models are trained on IBM’s curated, enterprise-focused data lake.

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AI AI Machine Learning Machine Learning 70

AWS Machine Learning Blog

DECEMBER 7, 2023

Given the availability of diverse data sources at this juncture, employing the CNN-QR algorithm facilitated the integration of various features, operating within a supervised learning framework. Utilizing Forecast proved effective due to the simplicity of providing the requisite data and specifying the forecast duration.

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AWS Algorithm Data Science Machine Learning 128

IBM Journey to AI blog

JUNE 14, 2023

With a foundation model, often using a kind of neural network called a “transformer” and leveraging a technique called self-supervised learning, you can create pre-trained models for a vast amount of unlabeled data. But that’s all changing thanks to pre-trained, open source foundation models.

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AI AI Natural Language Processing Data Lakes 103

AWS Machine Learning Blog

SEPTEMBER 5, 2023

Conclusion In this post, we showed how our team used AWS Glue and SageMaker to create a scalable supervised learning solution for predictive maintenance. Our model is capable of capturing trends across long-term histories of sensor data and accurately detecting hundreds of equipment failures weeks in advance. The remaining 8.4%

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AWS ML ML Machine Learning 120