Best Natural Language Processing Software for n8n

Machine learning can provide insightful text analysis that extracts, analyses, and stores text. AutoML allows you to create high-quality custom machine learning models without writing a single line. Natural Language API allows you to apply natural language understanding (NLU). To identify and label fields in a document, such as emails and chats, use entity analysis. Next, perform sentiment analysis to understand customer opinions and find UX and product insights. Natural Language with speech to text API extracts insights form audio. Vision API provides optical character recognition (OCR), which can be used to scan scanned documents. Translation API can understand sentiments in multiple languages. You can use custom entity extraction to identify domain-specific entities in documents. Many of these entities don't appear within standard language models. This allows you to save time and money by not having to do manual analysis. You can create your own machine learning custom models that can classify, extract and detect sentiment.

Amazon Textract, a fully managed machine-learning service, automatically extracts text from scanned documents. It goes beyond optical character recognition (OCR), to identify, understand and extract data from forms or tables. Today, many companies extract data from scanned documents such as PDF's and tables using manual data entry. This can be slow, expensive, and prone to errors. Or, they use OCR software which requires manual configuration and must be updated every time the form is modified to be usable. Textract uses machine-learning to automatically read and process any type document. It extracts text, forms, tables, and other data without any manual effort or custom code. Textract allows you to quickly automate manual document activities and process millions of pages in just hours.

Amazon Comprehend uses machine learning to discover insights and relationships in text. No prior machine learning experience is required. Your unstructured data can hold a treasure trove. Your unstructured data can provide valuable insights into customer sentiment. These include customer emails, product reviews, support tickets, social media and even advertising copy. How can you get there? Machine learning is able to identify specific items of interest within large swathes text (such finding company names in analyst report), and can also learn the sentiment hidden within language (identifying negative customer reviews or positive customer interactions with service agents). This is possible at a nearly limitless scale. Amazon Comprehend uses machine-learning to help you discover the relationships and insights in your unstructured data.