Managing AI and ML in the Enterprise
The AI and ML deployments are well underway, but for CXOs the biggest issue will be managing these initiatives, figuring out where the data science team fits in and figuring out what algorithms to buy vs. build.
The big takeaway is that the model training revolves around those first two items. Business reality usually isn’t considered.
To get the word out about Aible Advanced, Aible is launching a 30-minute AutoML challenge. In less than 30 minutes, Aible will create a predictive model based on a user’s proprietary data in their own AWS account. If Aible fails, users keep the model free of charge.
Related stories:
Executive’s guide to prescriptive analyticsResearch: Tech leaders are eager to implement prescriptive analyticsFree PDF download: How to win with prescriptive analyticsEnterprise AI in 2019: What you need to knowSurvey: Tech leaders cautiously approach artificial intelligence and machine learning projectsFree PDF download: Managing AI and ML in the enterpriseEnterprise AI and machine learning: Comparing the companies and applicationsThe true costs and ROI of implementing AI in the enterprise
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