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10 Key Trends of Digital Transformation in Healthcare in 2022

OTS Solutions

Just a decade ago, the use of augmented and virtual reality in healthcare was deemed science fiction. Animal testing can be reduced, and human clinical trials can be expedited using AR and VR (Virtual Reality) technology, referred to as “virtual patients” or “organs-on-a-chip.”

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The best AI, analytics, and big data conferences of 2021

TechBeacon

As in 2020, most conference organizers are once again opting to hold their events virtually, althoug some events scheduled for the latter half of the year are optimistically scheduled to be in-person events.

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A Brief Introduction to Big Data Applications and Hadoop

UruIT

Big data refers to the set of techniques used to store and/or process large amounts of data. . Usually, big data applications are one of two types: data at rest and data in motion. For this article, we’ll focus mainly on data at rest applications and on the Hadoop ecosystem specifically.

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What Big Data and Public Speaking Have in Common

CTOvision

Learning management systems are employing big data and even machine learning algorithms to create immersive virtual speaking environments. Big data analysis allows speakers and eLearning solutions to evaluate their own performance to provide greater customization, iterative improvements, and easier deployment.

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Companies betting on data must value people as much as AI

TechCrunch

Data holds much value, and businesses are very much aware of it, as showcased by the appetite for AI experts in non-tech companies. Data can enhance the operations of virtually any component within the organizational structure of any business. How to ensure data quality in the era of Big Data.

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Hadoop vs Spark: Main Big Data Tools Explained

Altexsoft

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work?

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

or greater): python3 -m venv.venv Activate the virtual environment: source.venv/bin/activate Install the AWS CDK, which is in the required Python dependencies: pip install -r requirements.txt Configure the Streamlit application Complete the following steps to configure the Streamlit application: In the docker_app directory, locate the config_file.py