This repository houses a collection of my natural language processing (NLP) projects, showcasing a variety of applications and experiments in the field. From sentiment analysis to language modeling, explore the power of NLP through my code. Feel free to use, modify, and contribute!
- Sentiment Analysis
- Named Entity Recognition
- Text Classification
- Language Modeling
- Encoder-Decoder Architecture with Attention
- Transformers
- Recurrent Neural Network
- Fine-tuning using HuggingFace
- Word Embeddings
- Machine Translation
- 🤖 Intelligent Conversational Chatbot
- Python
- TensorFlow
- PyTorch
- NLTK
- Trax
- Pandas
- Numpy
To run any of the projects in Google Colab, follow these simple steps:
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Open in Colab:
- Click on the "Open in Colab" at the top of any notebook.
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Set Up the Environment:
- If required, follow the instructions within the Colab notebook to set up any necessary environment or dependencies.
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Run the Code:
- Execute the code cells in the notebook one by one to observe the results or modify them as needed.
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Explore and Learn:
- Feel free to experiment with the code, modify parameters, and gain hands-on experience with natural language processing.
Note: Make sure to check the license information before using or modifying the code.
Happy coding! 🚀
Contributions, bug reports, and feature requests are welcome! Feel free to fork and submit pull requests.
- Deep Learning with Pytorch Step-by-Step by Daniel Voigt Godoy.
- A comprehensive guide to understanding and implementing NLP techniques in real-world applications. Covers key concepts, algorithms, and practical examples.
This repository is licensed under the MIT License - see the MIT License file for details.