1 min read

Data Roadblocks for AI – Most common challenges

There are lot of challenges to deal with data. But until enterprises have a healthy pipeline of quality data, and wisdom of the insights gleaned by AI/ML models are at risk.
Data Roadblocks for AI – Most common challenges

Dr. Sigal Shaked, Co-founder and CTO, at Datomize, discusses the best approach to overcome data challenges and achieve strong data governance. Sigal has extensive experience of more than 15 years working with data in different fields.

AI/ML models are starved for data

Largest barrier in AI implementation is the lack of usable and relevant data. Linear algorithms need hundreds of examples per class, while more complex algorithms need tens of thousands to millions of data sets.

When a model is trained with insufficient data, there is a high risk that it won’t work effectively when new data is added.

steps to overcome data challenges...Here's how

insideBIGDATA - insideBIGDATA: Clear, Concise Insights on Big Data Strategies
insideBIGDATA: Clear, Concise Insights on Big Data Strategies
source:https://insidebigdata.com/

#Data #Challenges #AI #MachineLearning #Solutions #Probyto #ProbytoAI

Subscribe and follow us for latest news in Data Science and Machine learning and stay updated!
Facebook: https://facebook.com/probyto
Twitter: https://twitter.com/probyto
LinkedIn: https://linkedin.com/company/probyto
Instagram: https://instagram.com/probyto