Amazon Kendra VS spaCy

I recommend you look deeper at LangChain if you are not already familiar with it. You can also look at the aws-samples Github page; they have some great examples to get you started. For example, you could add Amazon Kendra to the mix. Connect it with one of its many sources, like Atlassian Confluence, and set up Langchain to utilize the Kendra retriever. And now you have a chatbot that can answer questions based... - Source: dev.to / 7 months ago

If you're doing this on AWS they already have a really contained solution for this. I'm sure Azure has a similar solution. I'll assume AWS - if so, AWS Kendra is a good place to start. This will give you performant natural language understanding and enterprise search support. Then you just need to map the rest of your desired functions to core AWS solutions. Source: 12 months ago

> > One of the most important capabilities of Bedrock is how easy it is to customize a model. Customers simply point Bedrock at a few labeled examples in Amazon S3, and the service can fine-tune the model for a particular task without having to annotate large volumes of data (as few as 20 examples is enough) I can't even. Does anyone remember Amazon Kendra [1]? They promised the same there. "Here's an ML powered... - Source: Hacker News / about 1 year ago

Amazon Kendra is now FedRAMP High Compliant. Amazon Kendra is now authorized as FedRAMP High in AWS GovCloud (US-West) Region. Amazon Kendra is a highly accurate intelligent search service powered by machine learning. Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they are looking for, even when it's scattered across multiple... - Source: dev.to / over 1 year ago

It supports using Lambdas for fulfilling specific duties, such as placing orders, as well as integrating into Kendra which is a ML powered search service. You can effectively have a conversation asking for information and it can intelligently look through your business domain and respond with answers in a naturally conversational way. - Source: dev.to / over 1 year ago

Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):. - Source: dev.to / about 2 months ago

SpaCy: An open-source library providing tools for advanced NLP tasks like tokenization, entity recognition, and part-of-speech tagging. Source: 5 months ago

In this article, I'm going to walk through a sentiment analysis project from start to finish, using open-source Amazon product reviews. However, using the same approach, you can easily implement mass sentiment analysis on your own products. We'll explore an approach to sentiment analysis with one of the most popular Python NLP packages: spaCy. - Source: dev.to / 7 months ago

Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post. The steps... - Source: Hacker News / 8 months ago

I chose spacy. Although it's not state of the art, it's very well established and stable. Source: 10 months ago