Need advice about which tool to choose?Ask the StackShare community!

rasa NLU

123
282
+ 1
25
UBIAI

1
11
+ 1
0
Add tool

UBIAI vs rasa NLU: What are the differences?

UBIAI: An easy-to-use text annotation tool for NLP applications. It is an efficient and easy-to-use text annotation tool for Natural Language Processing (NLP) applications. With this, you can train an NLP model in few hours by collaborating with team members and using the machine learning auto-annotation feature; rasa NLU: Open source, drop-in replacement for NLP tools like wit.ai. rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

UBIAI and rasa NLU are primarily classified as "Data Labeling as a Service" and "NLP / Sentiment Analysis" tools respectively.

Some of the features offered by UBIAI are:

  • Multi-format document upload: TXT, CSV , JSON , PDF, DOC, HTML
  • Multilingual: English, French, German, Arabic, Spanish, etc…
  • Dictionary/Regex auto-annotation: input a list of words or regex patterns along with their associated entities. The tool will automatically scan the documents and auto-annotate

On the other hand, rasa NLU provides the following key features:

  • open source
  • python
  • NLP

rasa NLU is an open source tool with 9.66K GitHub stars and 2.98K GitHub forks. Here's a link to rasa NLU's open source repository on GitHub.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of rasa NLU
Pros of UBIAI
  • 9
    Open Source
  • 6
    Docker Image
  • 6
    Self Hosted
  • 3
    Comes with rasa_core
  • 1
    Enterprise Ready
    Be the first to leave a pro

    Sign up to add or upvote prosMake informed product decisions

    Cons of rasa NLU
    Cons of UBIAI
    • 4
      No interface provided
    • 4
      Wdfsdf
      Be the first to leave a con

      Sign up to add or upvote consMake informed product decisions

      What is rasa NLU?

      rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

      What is UBIAI?

      It is an efficient and easy-to-use text annotation tool for Natural Language Processing (NLP) applications. With this, you can train an NLP model in few hours by collaborating with team members and using the machine learning auto-annotation feature.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use rasa NLU?
      What companies use UBIAI?
        No companies found
        See which teams inside your own company are using rasa NLU or UBIAI.
        Sign up for StackShare EnterpriseLearn More

        Sign up to get full access to all the companiesMake informed product decisions

        What tools integrate with rasa NLU?
        What tools integrate with UBIAI?
          No integrations found

          Sign up to get full access to all the tool integrationsMake informed product decisions

          What are some alternatives to rasa NLU and UBIAI?
          Dialogflow
          Give users new ways to interact with your product by building engaging voice and text-based conversational apps.
          SpaCy
          It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
          NLTK
          It is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language.
          TensorFlow
          TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
          Transformers
          It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
          See all alternatives