Welcome to the Hindi Machine Learning Exploration repository ! This repository contains a collection of tools and techniques for machine learning tasks specifically tailored for the Hindi language. Here's an overview of the work done in this repository
- Data Cleaning : Removing links, emojis, and other non-textual elements to prepare the data for further processing.
- Stopwords Removal : Manually creating a stopwords list since there is no available Hindi stopwords library, filtering out common words that do not contribute to the meaning of the text.
- Stemming: Manually implementing stemming techniques as there is no inbuilt library for Hindi stemming, normalizing Hindi text data by reducing inflected words to their root forms. This includes manually created prefixes and suffixes to capture variations in word forms.
- Logistic Regression Utilizing logistic regression for binary classification tasks with Hindi text data.
- Passive Aggression Implementing the passive-aggressive algorithm for online learning in the context of Hindi language classification.
- Naive Bayes Leveraging the Naive Bayes classifier for efficient and effective classification of Hindi text data.
- SVM (Support Vector Machine) Utilizing SVM for classification tasks; although experiencing some errors, efforts are ongoing for resolution.
- Continuous Bag of Words (CBOW) Implementing the CBOW model for generating word embeddings from Hindi text data.
- Skip-gram Utilizing the skip-gram approach to generate word embeddings, enhancing representation learning for Hindi language.
- TF-IDF Representation Utilizing the TF-IDF weighting scheme to represent Hindi text data, capturing term importance in documents.
- Clone this repository to your local machine.
- Navigate to the desired script or notebook to explore individual techniques.
- Ensure you have the necessary dependencies installed.
- Experiment with the provided code, adapt it to your specific tasks, and contribute enhancements back to the community!
Contributions to this repository are welcome! If you have ideas for improvements, new features, or bug fixes, feel free to open an issue or submit a pull request.
This theoretical work is licensed under the Creative Commons Attribution 4.0 International License.
The Creative Commons Attribution 4.0 International License allows others to share and adapt the work for any purpose, even commercially, provided that proper credit is given to the original author.
For more details, please see the full text of the CC BY 4.0 license.
Special thanks to all contributors and open-source projects that have made this work possible.
Happy exploring with Hindi machine learning !