G2

KUNJAN M.

Freelancing

Small-Business (50 or fewer emp.)

7/15/2021

"Perfect package for NLP folks!"

5/5

What do you like best about Gensim?

Best tools for unsupervised learning, Topic and language modeling, document indexing, similarity retrieval with large corpora, Vector Space algorithms, and deep neural network supplementary tools such as NLTK, Keras, word2vec, FastText, etc. Compiled models, conda integration, API for maximizing the computations without depending on the high computational power. Visualization and model analysis is also provided that helps while developing the customized neural network models. Review collected by and hosted on G2.com.

What do you dislike about Gensim?

Optimized for platform independence but could be hectic to manage the codebase since the Gensim dependencies are separate from the independent stand-alone packages like TensorFlow, Keras, etc. Review collected by and hosted on G2.com.

Recommendations to others considering Gensim:

Must adapt to use the Gensim package if working on the NLP topic modeling with platform independence, fast computations, distributed computing support, and supportive community to debug and solve the problems occurring during the implementation. Review collected by and hosted on G2.com.

What problems is Gensim solving and how is that benefiting you?

Availability of word embeddings, compiled models, their methods, and documentation are the benefits. I found bit hectic while working on FastText since the separate FastText package is available and it is easy to follow their guide than Gensim. Working great with the conda installation. However, if installed separately, sometimes standalone TensorFlow and Numpy versions compatibility issues occurred. Review collected by and hosted on G2.com.