Remove Data Science Remove Predictive Modeling Remove Structured Data Remove Visualization
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How to create a Stroke Prediction Model?

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon INTRODUCTION: Stroke is a medical condition that can lead to the. The post How to create a Stroke Prediction Model? appeared first on Analytics Vidhya.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. Popular consumption entities in many organizations are queries, reports, and data science workloads.

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What is a customer data platform? A unified customer database

CIO Business Intelligence

Customer data platform defined. A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. Treasure Data CDP.

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What is a Data Pipeline?

Jet Global

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. For example, streaming data from sensors to an analytics platform where it is processed and visualized immediately.