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Artificial Intelligence

Machine Learning: Making AI Practical with Einstein

Cloud-based machine learning platforms are making machine learning and data-driven applications approachable to the layperson. Many people touch data in their jobs or could benefit from data-driven insights, but they don’t always have expertise in crunching data and extracting contextual insights from it. Shubha Nabar, Director of Data Science at Salesforce Einstein, spoke to TechTarget to explain how Einstein is democratizing AI for companies of every size and industry.

With features such as automated data cleansing, embedding explainability into machine learning models, and algorithms to detect and avoid bias, Einstein AI can point an employee to useful insights where they can take action without requiring a team of engineering, data science, and DevOps experts.

“One of the big advantages with Salesforce is that, with customer data and business applications all available on the platform, it’s possible for Salesforce to offer more low-code, tightly integrated experiences without a business needing its army of engineers and data scientists to apply machine learning to their data,” said Nabar.

Find out more about Einstein’s unique capabilities in the TechTarget interview.


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