AWS Machine Learning Blog

AUGUST 22, 2023

Machine learning (ML) is revolutionizing solutions across industries and driving new forms of insights and intelligence from data. Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed.

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Flipboard

MARCH 7, 2023

Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. Studio provides all the tools you need to take your models from data preparation to experimentation to production while boosting your productivity.

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Python AWS ML ML 122

The MLOps Blog

NOVEMBER 30, 2022

Data science teams currently struggle with managing multiple experiments and models and need an efficient way to store, retrieve, and utilize details like model versions, hyperparameters, and performance metrics. ML model versioning: where are we at? The short answer is we are in the middle of a data revolution.

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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). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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AWS Machine Learning Blog

APRIL 16, 2024

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them.

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DataRobot

SEPTEMBER 14, 2021

Since DataRobot was founded in 2012, we’ve been committed to democratizing access to the power of AI. We’re building a platform for all users: data scientists, analytics experts, business users, and IT. Let’s dive into each of these areas and talk about how we’re delivering the DataRobot AI Cloud Platform with our 7.2

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Heartbeat

AUGUST 21, 2023

AlexNet is a more profound and complex CNN architecture developed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton in 2012. The data should be split into training, validation, and testing sets. It has eight layers, five of which are convolutional and three fully linked. We pay our contributors, and we don’t sell ads.

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Tableau

FEBRUARY 24, 2021

As data science work grew in complexity, data scientists became less generalized and more specialized, often engaged in specific aspects of data science work. as early as 2012 already identified this trend, which has only accelerated over time. Interviews conducted by Harris et al.

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Tableau

FEBRUARY 24, 2021

As data science work grew in complexity, data scientists became less generalized and more specialized, often engaged in specific aspects of data science work. as early as 2012 already identified this trend, which has only accelerated over time. Interviews conducted by Harris et al.

Data Science 52

Data Science Data Scientist Data Visualization Computer Science 52