Implementation of Deep-learning techniques in pytorch
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Updated
Jun 16, 2019 - Jupyter Notebook
Implementation of Deep-learning techniques in pytorch
This repository contains introductory notebooks for text mining and web scrapping.
Jupyter Notebook for Natural Language Processing with Python. Please refer to the README.md file for the topics covered in this Notebook.
A jupyter notebook for topic-modelling, clustering and question-answering on COVID-19 research papers.
A notebook that contains a collection of NLP models that automatically score essays
Contains relevant notebooks for the hands-on NLP workshop by organized Analytics India Magazine Plugin Conference-2020 Edition
The ipython notebook is working to build a model which will detect duplicate questions if two questions pair are given.
The repository contains notebooks created for collecting and preprocessing the corpus of diary entries and for experiments on creating models for predicting gender, age groups of authors and the time period of text creation.
This notebook is trying to build a model which will recommend the movie based on given movie and genre. In this we use Popularity Based Recommendation, Content Based Recommendation and Collaborative Filtering based Recommendation.
Coursework project for STINTSY with the task of classifying excerpts according to who authored them. The Jupyter Notebook contains the ML text classification pipeline as well as a comprehensive documentation of the methodology and experiments done to achieve the best results.
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