rasa NLU vs FastText | What are the differences? | StackShare

FastText vs rasa NLU

Overview

rasa NLU

Stacks120

Followers282

Votes25

FastText

Stacks37

Followers65

Votes1

GitHub Stars26.4K

Forks4.8K

rasa NLU vs FastText: What are the differences?

What is 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.

What is FastText? Library for efficient text classification and representation learning. 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.

rasa NLU and FastText can be primarily classified as "NLP / Sentiment Analysis" tools.

rasa NLU is an open source tool with 6.58K GitHub stars and 2.01K GitHub forks. Here's a link to rasa NLU's open source repository on GitHub.

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Detailed Comparison

rasa NLU	FastText
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.	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.
Open source; NLP; Machine learning	Train supervised and unsupervised representations of words and sentences; Written in C++
Statistics
GitHub Stars -	GitHub Stars 26.4K
GitHub Forks -	GitHub Forks 4.8K
Stacks 120	Stacks 37
Followers 282	Followers 65
Votes 25	Votes 1
Pros & Cons
Pros 9 Open Source 6 Docker Image 6 Self Hosted 3 Comes with rasa_core 1 Enterprise Ready Cons 4 No interface provided 4 Wdfsdf	Pros 1 Simple Cons 1 No in-built performance plotting facility or to get it 1 No step by step API support 1 No step by step API access
Integrations
Slack RocketChat Google Hangouts Chat Telegram Microsoft Bot Framework Twilio Mattermost	Python C++ macOS C#

What are some alternatives to rasa NLU, FastText?

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.

Speechly

It can be used to complement any regular touch user interface with a real time voice user interface. It offers real time feedback for faster and more intuitive experience that enables end user to recover from possible errors quickly and with no interruptions.

MonkeyLearn

Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.

Jina

It is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.

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.

CoreNLP

It provides a set of natural language analysis tools written in Java. It can take raw human language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize and interpret dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases or word dependencies, and indicate which noun phrases refer to the same entities.

Flair

Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification.

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.

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 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.