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NLTK vs Theano: 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, Theano is detailed as "Define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently". Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray). Using Theano it is possible to attain speeds rivaling hand-crafted C impleme.

NLTK and Theano can be primarily classified as "Machine Learning" tools.

Theano is an open source tool with 8.87K GitHub stars and 2.5K GitHub forks. Here's a link to Theano's open source repository on GitHub.

According to the StackShare community, NLTK has a broader approval, being mentioned in 15 company stacks & 17 developers stacks; compared to Theano, which is listed in 5 company stacks and 10 developer stacks.

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What are some alternatives to ?

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.

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.

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