Category Archive

Below you'll find a list of all posts that have been categorized as “gensim”

Pivoted document length normalisation

Mohit Rathore 2018-06-19 gensim, Student Incubator

As a part of the RARE incubator program my goal was to add two new features on the existing TF-IDF model of Gensim. One was implementing a SMART information retrieval system (smartirs) scheme [1] and the other was implementing pivoted document length normalization [2].

Sent2Vec: An unsupervised approach towards learning sentence embeddings

Prerna Kashyap 2018-06-19 gensim, Student Incubator

A comparison of sentence embedding techniques by Prerna Kashyap, our RARE Incubator student. As her graduation project, Prerna implemented sent2vec, a new document embedding model in Gensim, and compared it to existing models like doc2vec and fasttext.

Docstrings in open source Python

Dmitry Berdov 2018-06-18 gensim, Open Source, Student Incubator

Hi everyone, my name is Dmitry Berdov, I’m a graduate student at the Ural Federal University, now working in QA testing (automation) sphere. I had no experience with writing documentation before joining the RARE Incubator, where my task has been to refactor and improve the poor state of Gensim docs. Now, after several months of shooting myself hard in the ...

Gensim Survey 2018

Radim Řehůřek 2018-04-30 gensim, Machine Learning, Open Source

Last month, we ran a survey among Gensim users to get a better idea what delights and annoys you. The ~7 minute survey was completed by 448 people. That’s a great juicy sample, big thanks to all who participated! Full detailed statistics here; in this post I’ll summarize what we found and what it means for Gensim.

Implementing Poincaré Embeddings

Jayant Jain 2017-12-09 gensim, Open Source 3 Comments

I have been working on implementing a model called Poincaré embeddings over the last month or so. The model is from an interesting paper by Facebook AI Research – Poincaré Embeddings for Learning Hierarchical Representations [1]. This post describes the model at a relatively high level of abstraction, and the detailed technical challenges faced in the process of implementing it.

Output for python -m gensim.downloader --info

New download API for pretrained NLP models and datasets in Gensim

Chaitali Saini 2017-11-27 Datasets, gensim, Open Source, Student Incubator 3 Comments

There’s no shortage of websites and repositories that aggregate various machine learning datasets and pre-trained models (Kaggle, UCI MLR, DeepDive, individual repos like gloVe, FastText, Quora, blogs, individual university pages…). The only problem is, they all use widely different formats, cover widely different use-cases and go out of service with worrying regularity. For this reason, we decided to include free …

Translation Matrix: how to connect “embeddings” in different languages?

Ji Xiaohong 2017-09-13 gensim, Student Incubator

This is a blog post by one of our Incubator students, Ji Xiaohong. Ji worked on the problem of aligning differently trained word embeddings (such as word2vec), which is useful in applications such as machine translation or tracking language evolution within the same language.

Chinmaya’s GSoC 2017 Summary: Integration with sklearn & Keras and implementing fastText

Chinmaya Pancholi 2017-09-02 gensim, Google Summer of Code, Student Incubator

This blog summarizes the work that I did for Google Summer of Code 2017 with Gensim. My work during the summer was divided into two parts: integrating Gensim with scikit-learn & Keras and adding a Python implementation of fastText model to Gensim. Gensim integration with scikit-learn and Keras Gensim is a topic modelling and information extraction library which mainly serves unsupervised …

Parul’s GSoC 2017 summary: Training and Topic visualizations in gensim

Parul Sethi 2017-08-29 gensim, Google Summer of Code, Open Source

This blog post summarizes my work done during the Google Summer of Code 2017. My task was to implement topic modeling visualizations which could help users to interactively analyze their topic models and get the best out of their data. I worked on adding two types of visualizations: 1. To monitor the training process of LDA with the help of …

Chinmaya’s Google Summer of Code 2017 Live-Blog : a Chronicle of Integrating Gensim with scikit-learn and Keras

Chinmaya Pancholi 2017-06-12 gensim, Student Incubator

2nd September, 2017 The final blogpost in the GSoC 2017 series summarising all the work that I did this summer can be found here. 15st August, 2017 During the last two weeks, I had been working primarily on adding a Python implementation of Facebook Research’s Fasttext model to Gensim. I was also simultaneously working on completing the tasks left for adding scikit-learn API for …

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