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NLTK

95
131
+ 1
0
SpaCy

177
226
+ 1
11
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NLTK vs SpaCy: What are the differences?

Developers describe NLTK as "It is a leading platform for building Python programs to work with human language data". It is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language. On the other hand, SpaCy is detailed as "Industrial-Strength Natural Language Processing in Python". 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 can be classified as a tool in the "Machine Learning Tools" category, while SpaCy is grouped under "NLP / Sentiment Analysis".

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Pros of NLTK
Pros of SpaCy
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    • 10
      Speed
    • 1
      No vendor lock-in

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    Cons of NLTK
    Cons of SpaCy
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        Requires creating a training set and managing training

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      What is NLTK?

      It is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language.

      What is 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.

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

      What companies use NLTK?
      What companies use SpaCy?
      See which teams inside your own company are using NLTK or SpaCy.
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      What tools integrate with NLTK?
      What tools integrate with SpaCy?
      What are some alternatives to NLTK and SpaCy?
      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.
      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.
      PyTorch
      PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
      scikit-learn
      scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
      Keras
      Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
      See all alternatives