In the world of AI and predictive analytics, BERT isn’t a person but a machine learning, open source framework for Natural Language Processing (NLP).
BERT, which stands for Bidirectional Encoder Representations from Transformers, is designed to help computers understand the meaning and impact of language in text. It was developed and published by Google as an open-source solution in 2018. By late 2020 BERT was powering almost every English-based query on Google Search. It’s now known for being the industry standard used by leading companies around the world.
One of the reasons BERT is such a powerful tool is the amount of pre-training it went through. BERT was originally pre-trained on the whole of the English Wikipedia and Brown Corpus, which it can draw from as it continues to learn on new data sources (your data sources).
BERT is one of the NLP techniques layered along with our own priority techniques that Squark automatically applies to your analysis to determine what words have an impact on outcomes.
What use cases can NLP help you figure out?
As powerful as BERT is, it is just one of the advanced feature engineering techniques that Squark automatically applies to every project. Our team keeps up with all the latest trends and advances and adds them to our platform, so our users are confident they are using the most cutting-edge methods.
Takeaway: The technology for computers using machine learning to determine language and its effect on outcomes now exists, and its name is BERT.
Reach out today to schedule a demo and discuss your company’s use cases.
Squark is a no-code predictive analytics SaaS that automatically analyzes business data you work with every day to predict customer outcomes, uncover new and unforeseen business opportunities, and mitigate risk. It is a simple and easy-to-use AI software that doesn’t require data science nor technical expertise. In a matter of clicks, make confident, data-backed decisions about what your customers will do next and understand why to increase your business impact.