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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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Time-Series Forecasting Using Attention Mechanism

Analytics Vidhya

Introduction Time-series forecasting plays a crucial role in various domains, including finance, weather prediction, stock market analysis, and resource planning. Accurate predictions can help businesses make informed decisions, optimize processes, and gain a competitive edge.

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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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Forecasting Solar Radiation using DataRobot to Optimize Power Generation

DataRobot Blog

There is a need to optimize supply to meet demand. One way to determine if supply can meet demand is to forecast how much solar power can be generated in advance. Forecasting how much solar power will be generated is directly dependent on the availability of solar radiation or sunlight in layman terms. DataRobot Core.

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The Best Sales Forecasting Models for Weathering Your Goals

Every sales forecasting model has a different strength and predictability method. This way, you’ll be able to further enhance – and optimize – your newly-developed pipeline. Your future sales forecast? It’s recommended to test out which one is best for your team. Sunny skies (and success) are just ahead!

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What is cloud cost optimization?

IBM Big Data Hub

However, cloud services costs can be higher than anticipated, so monitoring and optimizing your cloud spend is critical. Cloud cost optimization combines strategies, techniques, best practices and tools to help reduce cloud costs, find the most cost-effective way to run your applications in the cloud environment, and maximize business value.

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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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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.