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Travel Analytics: Data Sources, Use Cases, and Real-Life Examples

Altexsoft

Beyond its fundamental role in elevating customer experience, travel analytics has a valuable impact on revenue growth and cultivating a competitive edge. This article explores the influence of analytics on marketing strategies, revenue management, guest personalization, and other aspects of the travel industry.

Travel 52
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How ML System Design helps us to make better ML products

Xebia

With the industry moving towards end-to-end ML teams to enable them to implement MLOPs practices, it is paramount to look past the model and view the entire system around your machine learning model. A demand forecasting case will be used to demonstrate the process.

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How Industry 4.0 Changes Predictive Maintenance From Mobile Apps And What It Means For The Future ?

OTS Solutions

has been transforming the manufacturing sector through the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data analytics. These technologies allow mobile apps to learn and adapt to specific equipment conditions, further reducing the risk of equipment failures. Industry 4.0

Mobile 130
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AI & Business Analytics: A Smart Guide

Sunflower Lab

Diving into World of Business Analytics Data analytics is not an old concept, it is an essential practice which has driven business success in the past and the present, it will confidently drive the success in the future too. “ Data Explosion ” refers to a trend of exponentially multiplying data that is stored.

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Unlocking accuracy, efficiency and agility through Continuous Touchless Demand Forecasting

Capgemini

Continuous Touchless Demand Forecasting is defined by Capgemini Invent as a capability that capitalizes on Big Data, Artificial Intelligence, and Machine Learning to “ recognize historical patterns, select best-fit statistical models, and draw on a variety of inputs and forward-looking variables, (.)

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A Comprehensive Guide: What are the most popular Machine Learning Tools in 2023?

Openxcell

Machine Learning has noticed rapid growth—resulting in the creation of numerous tools and platforms for creating, evaluating, and deploying Machine Learning Models. The most popular Machine Learning tools have earned wide adoption in different industry settings and have active user and contributor groups.

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How Machine Learning is Used in Finance and Banking

Exadel

Financial institutions, in particular, need to stay ahead of the curve using cutting-edge technology to optimize their IT and meet the latest market demands. The banking landscape is constantly changing, and the application of machine learning in banking is arguably still in its early stages.