The Jupyter notebook is a web-based notebook environment for interactive computing. 

The fundamental package for scientific computing with Python.

Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics. 

Gensim 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. All algorithms are memory-independent w.r.t. the corpus size (can process input larger than RAM, streamed, out-of-core), Intuitive interfaces  easy to plug in your own input corpus/datastream (trivial streaming API) easy to extend with other Vector Space algorithms (trivial transformation API) Efficient multicore implementations of popular algorithms, such as online Latent Semantic Analysis (LSA/LSI/SVD), Latent Dirichlet Allocation (LDA), Random Projections (RP), Hierarchical Dirichlet Process (HDP) or word2vec deep learning. Distributed computing: can run Latent Semantic Analysis and Latent Dirichlet Allocation on a cluster of computers. Extensive documentation and Jupyter Notebook tutorials. 

GloVe model for distributed word representation

We provide an implementation of the GloVe model for learning word representations, and describe how to download web-dataset vectors or train your own. See the project page or the paper for more information on glove vectors. 

💫 Industrial-strength Natural Language Processing (NLP) in Python

spaCy 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. spaCy comes with pretrained pipelines and currently supports tokenization and training for 60+ languages. It features state-of-the-art speed and neural network models for tagging, parsing, named entity recognition, text classification and more, multi-task learning with pretrained transformers like BERT, as well as a production-ready training system and easy model packaging, deployment and workflow management. spaCy is commercial open-source software, released under the MIT license. Support for 60+ languages Trained pipelines for different languages and tasks Multi-task learning with pretrained transformers like BERT Support for pretrained word vectors and embeddings State-of-the-art speed Production-ready training system Linguistically-motivated tokenization Components for named entity recognition, part-of-speech-tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking and more Easily extensible with custom components and attributes Support for custom models in PyTorch, TensorFlow and other frameworks Built in visualizers for syntax and NER Easy model packaging, deployment and workflow management Robust, rigorously evaluated accuracy 

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notebookby jupyter

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numpyby numpy

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seabornby mwaskom

seabornby mwaskom

scipyby scipy

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matplotlibby matplotlib

matplotlibby matplotlib

gensimby RaRe-Technologies

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GloVeby stanfordnlp

GloVeby stanfordnlp

spaCyby explosion

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