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Machine Learning Approach to Forecast Cars’ Demand

Analytics Vidhya

Introduction on Machine Learning Last month, I participated in a Machine learning approach Hackathon hosted on Analytics Vidhya’s Datahack platform. The post Machine Learning Approach to Forecast Cars’ Demand appeared first on Analytics Vidhya. In this article, I will […].

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SAP forecasts clarity in the cloud

CIO Business Intelligence

And even the companies that have heavily invested in SAP on-premise for years are moving to the cloud, with Microsoft Teams and Microsoft 365 — best-of-breed applications — or they host their ERP systems. That’s why I advise against simply replicating old processes into the new software world, or just hosting the ERP upgrade.

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The Struggle Between Data Dark Ages and LLM Accuracy

Cloudera

The AI Forecast: Data and AI in the Cloud Era , sponsored by Cloudera, aims to take an objective look at the impact of AI on business, industry, and the world at large. Dont forget to tune in to Spotify or Apple Podcasts to listen to future episodes of The AI Forecast: Data and AI in the Cloud Era. But what does that future look like?

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The 10 Essential SaaS Trends You Should Watch Out For In 2020

datapine

Even if figures diverge somewhat, the many forecasts conducted on SaaS industry trends 2020 demonstrate an obvious reality: the SaaS market is going to get bigger and bigger. SaaS Industry is forecasted to reach $55 billion by 2026. Our second forecast for SaaS trends in 2020 is Vertical SaaS. 2) Vertical SaaS. 6) Micro-SaaS.

Software 314
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Akeneo aims to transform the retail playbook with AI and data consistency

CIO Business Intelligence

According to Retail Doctor Groups latest research , Australian retailers demonstrate a sophisticated understanding of AI applications, particularly in personalisation, demand forecasting, and supply chain optimisation. Since then, its online customer return rate dropped from 10% to 1.6%

B2B 105
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Marsh McLennan IT reorg lays foundation for gen AI

CIO Business Intelligence

Several co-location centers host the remainder of the firm’s workloads, and Marsh McLennans big data centers will go away once all the workloads are moved, Beswick says. Marsh McLennan has been using ML algorithms for several years for forecasting, anomaly detection, and image recognition in claims processing.

IT 122
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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Domino’s Pizza, for instance, uses operational demand forecasting to deliver on its ‘ 30 minutes or less’ policy – a USP that has cemented the brand’s success in a saturated marketplace. Where is all of that data going to come from? This is a testament to the brand-boosting power of big data in logistics.

Big Data 275