DagsHub

FEBRUARY 29, 2024

Data, is therefore, essential to the quality and performance of machine learning models. This makes data preparation for machine learning all the more critical, so that the models generate reliable and accurate predictions and drive business value for the organization. Why do you need Data Preparation for Machine Learning?

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AWS Machine Learning Blog

NOVEMBER 27, 2023

Generative artificial intelligence ( generative AI ) models have demonstrated impressive capabilities in generating high-quality text, images, and other content. However, these models require massive amounts of clean, structured training data to reach their full potential. Clean data is important for good model performance.

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Dataconomy

JULY 28, 2023

Data preprocessing is a fundamental and essential step in the field of sentiment analysis, a prominent branch of natural language processing (NLP). Data scientists must decide on appropriate strategies to handle missing values, such as imputation with mean or median values or removing instances with missing data.

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Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Tableau

MAY 6, 2021

Check out our five #TableauTips on how we used data storytelling, machine learning, natural language processing, and more to show off the power of the Tableau platform. . Let AI do the heavy lifting . Einstein sifted through the data, discovered patterns, and surfaced recommendations in natural language.

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Tableau

MAY 6, 2021

Check out our five #TableauTips on how we used data storytelling, machine learning, natural language processing, and more to show off the power of the Tableau platform. . Let AI do the heavy lifting . Einstein sifted through the data, discovered patterns, and surfaced recommendations in natural language.

Tableau 52

Tableau Natural Language Processing Machine Learning Machine Learning 52

DataRobot Blog

SEPTEMBER 11, 2019

Yet most FP&A analysts & management spend the vast majority of their time on that preliminary work—reconciliation, analysis, cleansing, and standardization, which I’ll refer to here collectively as data preparation. That’s because Microsoft Excel is still the go-to tool for performing all of that data prep. The hard way.

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