By Vicky Stavropoulou, contributing writer for Citylife.capetown
The 21st century has seen a significant shift in the way we approach agriculture, with the advent of new technologies and the growing need to feed an ever-increasing global population. One such technology that has gained considerable attention in recent years is predictive analytics. This powerful tool has the potential to revolutionize the agricultural industry by enabling farmers to make data-driven decisions, optimize resource utilization, and ultimately, increase crop yields and profitability.
By Lalitha Sundaramurthy, contributing writer for Sdcexec.com
In recent years, companies have invested in technologies that help them integrate analytics across the entire enterprise, with a goal of capturing the more than $9.5 trillion in business value that the McKinsey Global Institute estimates could be unlocked with full integration of advanced analytic.
By Natesh Babu Arunachalam, contributing writer for Kdnuggets.com
Many data science projects don’t see the light of the day. MLOps is a process that spans from the data stage to deployment stage and ensures the success of machine learning models. In this post, you will learn about the key stages in MLOps (from a data scientist’s perspective) along with some common pitfalls.
By Greg Kihlstrom contributing writer for Martech.com
In this four-part series, we’re exploring four categories of artificial intelligence (AI), how they can meaningfully impact marketers and their customers and what to potentially avoid. Part one (Generative AI) is here.
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