Alternatives to Thematic logo

Alternatives to Thematic

SpaCy, Transformers, rasa NLU, Gensim, and Amazon Comprehend are the most popular alternatives and competitors to Thematic.
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What is Thematic and what are its top alternatives?

The fastest and most reliable way for finding deep insights in NPS, CSAT, user research surveys and chat logs.
Thematic is a tool in the NLP / Sentiment Analysis category of a tech stack.

Top Alternatives to Thematic

  • SpaCy
    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. ...

  • Transformers
    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. ...

  • rasa NLU
    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. ...

  • Gensim
    Gensim

    It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community. ...

  • Amazon Comprehend
    Amazon Comprehend

    Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications. ...

  • Google Cloud Natural Language API
    Google Cloud Natural Language API

    You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage on Google Cloud Storage. ...

  • Sentence Transformers
    Sentence Transformers

    It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks. ...

  • FastText
    FastText

    It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices. ...

Thematic alternatives & related posts

SpaCy logo

SpaCy

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Industrial-Strength Natural Language Processing in Python
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PROS OF SPACY
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    Speed
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    No vendor lock-in
CONS OF SPACY
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    Requires creating a training set and managing training

related SpaCy posts

Transformers logo

Transformers

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State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0
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PROS OF TRANSFORMERS
    Be the first to leave a pro
    CONS OF TRANSFORMERS
      Be the first to leave a con

      related Transformers posts

      rasa NLU logo

      rasa NLU

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      Conversational AI platform, for personalized conversations at scale
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      PROS OF RASA NLU
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        Open Source
      • 6
        Docker Image
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        Self Hosted
      • 3
        Comes with rasa_core
      • 1
        Enterprise Ready
      CONS OF RASA NLU
      • 4
        No interface provided
      • 4
        Wdfsdf

      related rasa NLU posts

      Gensim logo

      Gensim

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      A python library for Topic Modelling
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      PROS OF GENSIM
        Be the first to leave a pro
        CONS OF GENSIM
          Be the first to leave a con

          related Gensim posts

          Biswajit Pathak
          Project Manager at Sony · | 6 upvotes · 808.2K views

          Can you please advise which one to choose FastText Or Gensim, in terms of:

          1. Operability with ML Ops tools such as MLflow, Kubeflow, etc.
          2. Performance
          3. Customization of Intermediate steps
          4. FastText and Gensim both have the same underlying libraries
          5. Use cases each one tries to solve
          6. Unsupervised Vs Supervised dimensions
          7. Ease of Use.

          Please mention any other points that I may have missed here.

          See more
          Amazon Comprehend logo

          Amazon Comprehend

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          Discover insights and relationships in text
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          PROS OF AMAZON COMPREHEND
            Be the first to leave a pro
            CONS OF AMAZON COMPREHEND
            • 2
              Multi-lingual

            related Amazon Comprehend posts

            Google Cloud Natural Language API logo

            Google Cloud Natural Language API

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            Derive insights from unstructured text using Google machine learning
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            PROS OF GOOGLE CLOUD NATURAL LANGUAGE API
              Be the first to leave a pro
              CONS OF GOOGLE CLOUD NATURAL LANGUAGE API
              • 2
                Multi-lingual

              related Google Cloud Natural Language API posts

              Sentence Transformers logo

              Sentence Transformers

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              Multilingual sentence, paragraph, and image embeddings
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              PROS OF SENTENCE TRANSFORMERS
                Be the first to leave a pro
                CONS OF SENTENCE TRANSFORMERS
                  Be the first to leave a con

                  related Sentence Transformers posts

                  FastText logo

                  FastText

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                  Library for efficient text classification and representation learning
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                  PROS OF FASTTEXT
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                    Simple
                  CONS OF FASTTEXT
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                    No step by step API support
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                    No in-built performance plotting facility or to get it
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                    No step by step API access

                  related FastText posts

                  Biswajit Pathak
                  Project Manager at Sony · | 6 upvotes · 808.2K views

                  Can you please advise which one to choose FastText Or Gensim, in terms of:

                  1. Operability with ML Ops tools such as MLflow, Kubeflow, etc.
                  2. Performance
                  3. Customization of Intermediate steps
                  4. FastText and Gensim both have the same underlying libraries
                  5. Use cases each one tries to solve
                  6. Unsupervised Vs Supervised dimensions
                  7. Ease of Use.

                  Please mention any other points that I may have missed here.

                  See more