A set of algorithms to build resources through lexicon generation for resource scarce languages.
-
Updated
Jan 3, 2021 - Jupyter Notebook
#
hindi-sentiment-analysis
Here are 3 public repositories matching this topic...
This project showcases a dataset of Amazon Reviews in Hindi, which we created ourselves. We applied various machine learning methods including Naive Bayes, SVM, and Decision Tree, using both Bag-of-Words and TF-IDF. Additionally, we experimented with deep learning techniques such as Feedforward Neural Networks and LSTM with ELMO embeddings.
machine-learning svm naive-bayes-classifier logistic-regression feedforward-neural-network tf-idf lstm-neural-networks multi-class-classification iiith hindi-sentiment-analysis decission-tree-classifier amazon-hindi-reviews niave
-
Updated
May 9, 2024 - Jupyter Notebook
Hindi Tweet Sentiment Analysis project predicts sentiment of Hindi tweets (Positive/Negative) using TF-IDF and classifiers like SVM, Random Forest, Naive Bayes, and Logistic Regression. Deployed via Gradio for real-time predictions.
nlp data-science machine-learning sentiment-analysis text-classification scikit-learn exploratory-data-analysis tf-idf feature-engineering tweet-analysis classification-models hindi-sentiment-analysis gradiodeployment
-
Updated
Apr 29, 2026 - Jupyter Notebook
Improve this page
Add a description, image, and links to the hindi-sentiment-analysis topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the hindi-sentiment-analysis topic, visit your repo's landing page and select "manage topics."