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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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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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4 key steps for optimizing your IT services portfolio

CIO Business Intelligence

From the CEO’s perspective, an optimized IT services portfolio maximizes cost efficiency, flexibility, and scalability. Highly optimized portfolios leverage outsourcing to ensure that commodity-based sourcing is offloaded to outsourcers, freeing up internal teams to focus on strategic projects that add value and effectively manage costs.

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Oracle Advances its AI-Enabled Supply Chain Management Suite

David Menninger's Analyst Perspectives

Predictive analytics also can be used to signal when forecasts or forecast components diverge from plan, allowing enterprises to react to changing circumstances sooner and with greater accuracy and coordination. This helps them maintain optimal inventory levels, reducing costs as well as the risk of overstocking or stockouts.

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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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MRO spare parts optimization

IBM Big Data Hub

Many asset-intensive businesses are prioritizing inventory optimization due to the pressures of complying with growing industry 4.0 2 Unless your demand forecasting is accurate, adopting a reactive approach might prove less efficient. Do you have purpose-built algorithms to improve intermittent and variable demand forecasting?

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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

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