GitHub / 2607amit / Text-Classification-using-Machine-Learning
# Text-Classification-using-Machine-Learning Building a multiclass Text Classification Model from scratch without using the inbuilt Sklearn model in order to identify which among the twenty categories a particular document belongs. A lot of data preprocessing is also performed in this project . And finally the built model's performance is compared with the inbuilt sklearn model's performance.
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PURL: pkg:github/2607amit/Text-Classification-using-Machine-Learning
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Forks: 0
Open issues: 0
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Language: Jupyter Notebook
Size: 16.2 MB
Dependencies parsed at: Pending
Created at: over 3 years ago
Updated at: over 3 years ago
Pushed at: over 3 years ago
Last synced at: 4 months ago
Topics: data-analysis, data-mining, data-preprocessing, machine-learning, multinomial-naive-bayes, naive-bayes-classifier, prediction, python, sklearn