What is gensim and where to use it
This recipe explains what is gensim library in python and where can we use it
Recipe Objective: What is Gensim and where to use it?
Gensim ("Generate Similar") is a python-based open-source framework for unsupervised topic modeling and natural language processing. It's a tool for extracting semantic concepts from documents, and it can handle extensive text collections. As a result, it distinguishes itself from other machine learning software packages that focus on memory processing. Gensim also provides efficient multicore implementations for several algorithms to improve processing speed. It has more text processing features than other packages like Scikit-learn, R, etc.
Hands-On Approach to Topic Modelling in Python
It performs various complex tasks using best models and contemporary statistical machine learning, including Creating word or document vectors.
Identification of the topic
Compare and contrast papers (retrieving semantically similar documents)
Detecting semantic structure in plain-text materials
Gensim has been used in a large number of applications, and a few of them include-
Word2vec
fastText
Latent Semantic Analysis (LSA)
Latent Dirichlet Allocation (LDA)
Term Frequency-Inverse Document Frequency (TF-IDF)
All of these are explained in detail in the further recipes.
What Users are saying..
Abhinav Agarwal
I come from Northwestern University, which is ranked 9th in the US. Although the high-quality academics at school taught me all the basics I needed, obtaining practical experience was a challenge.... Read More