Labelf AI aims to let anyone, no matter previous knowledge, create and use AI text classification models. We use an advanced approach to active learning to accelerate training on both labeled and unlabeled data. Can also be used for data analysis and will hook into most Customer support systems. Can be used for Document Classification, Automated Product Tagging, Automatic Support Ticket Tagging, Chat and Forum Moderation, Social Listening, Survey Analysis, Sales Stage Identification, Finding Sales leads and much more. Labelf models can also classify texts in any language despite having only been trained on data in one language.
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Based on our record, TabNine seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This is the repository for the backend of TabNine, the all-language autocompleter There are no source files here because the backend is closed source. - Source: dev.to / 9 days ago
As applications grow in value to the end user so do they grow in complexity. Developers are pressured to increase productivity. Startups like Tabnine and Raycast have had impressive funding rounds recently, indicating how important developer productivity has become. With this pressure to perform, developers don't have the time to test each API connection for vulnerabilities or perform periodical penetration... - Source: dev.to / over 2 years ago
We also use rust to build Tabnine! (see https://tabnine.com). Source: about 3 years ago
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