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Gensim vs Keras: What are the differences?
What is Gensim? A python library for Topic Modelling. 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.
What is Keras? Deep Learning library for Theano and TensorFlow. Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/.
Gensim can be classified as a tool in the "NLP / Sentiment Analysis" category, while Keras is grouped under "Machine Learning Tools".
Gensim and Keras are both open source tools. It seems that Keras with 43.2K GitHub stars and 16.5K forks on GitHub has more adoption than Gensim with 9.65K GitHub stars and 3.52K GitHub forks.
StyleShare Inc., Home61, and Suggestic are some of the popular companies that use Keras, whereas Gensim is used by MailMine.io, Mho, and Avito. Keras has a broader approval, being mentioned in 70 company stacks & 257 developers stacks; compared to Gensim, which is listed in 3 company stacks and 5 developer stacks.
Pros of Gensim
Pros of Keras
- Easy and fast NN prototyping7
- Quality Documentation7
- Supports Tensorflow and Theano backends6
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Cons of Gensim
Cons of Keras
- Hard to debug3