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How to Use XGBoost for Time-Series Forecasting?

Analytics Vidhya

Introduction Time-series forecasting is a crucial task in various domains, including finance, sales, and energy demand. Accurate forecasting allows businesses to make informed decisions, optimize resources, and plan for the future effectively. appeared first on Analytics Vidhya.

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Gartner projects major IT spending increases for 2025

CIO Business Intelligence

By 2026, hyperscalers will have spent more on AI-optimized servers than they will have spent on any other server until then, Lovelock predicts. Still, after 2028, it will be difficult to buy a device that isn’t AI optimized. Gartner is projecting worldwide IT spending to jump by 9.3% Gartner’s new 2025 IT spending projection , of $5.75

IT 133
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Deep Learning for Time Series Forecasting: Is It Worth It?

Dataiku

Time series forecasting use cases are certainly the most common time series use cases, as they can be found in all types of industries and in various contexts. Using RNNs & DeepAR Models to Find Out.

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Marsh McLennan IT reorg lays foundation for gen AI

CIO Business Intelligence

It’s a full-fledged platform … pre-engineered with the governance we needed, and cost-optimized. Marsh McLennan has been using ML algorithms for several years for forecasting, anomaly detection, and image recognition in claims processing. The idea, Beswick says, was to enable the creation of an application in days — which set a.

IT 122
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Easily Build an Optimization App and Empower Your Data

Speaker: Gertjan de Lange

If the last few years have illustrated one thing, it’s that modeling techniques, forecasting strategies, and data optimization are imperative for solving complex business problems and weathering uncertainty. Experience how efficient you can be when you fit your model with actionable data. Don't let uncertainty drive your business.

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Marsh McLellan IT reorg lays foundation for gen AI

CIO Business Intelligence

It’s a full-fledged platform … pre-engineered with the governance we needed, and cost-optimized. Marsh McLellan has been using ML algorithms for several years for forecasting, anomaly detection, and image recognition in claims processing. The idea, Beswick says, was to enable the creation of an application in days — which set a.

IT 105
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Is Data Analytics Ushering in the Modern Age of Weather Forecasting?

Smart Data Collective

Weather forecasting technology has grown from strength to strength in the last few decades. Gone are the days when you had to wait for the local news channel to share the weather forecasts for the next day. But if there’s one technology that has revolutionized weather forecasting, it has to be data analytics.