Welcome to our thrilling GitHub repository dedicated to Natural Language Processing (NLP) and Sentiment Analysis. Join us on an exhilarating journey as we dive deep into the realm of analyzing IMDB movie reviews, unraveling the emotions concealed within the text!
If you are new to GitHub click here to view the project.
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Inside this repository, you'll discover an extraordinary array of sentiment analysis techniques and models designed to extract the true essence of emotions from text data. Brace yourself for a mind-bending experience with these cutting-edge approaches:
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Multinomial Bayes: Embark on a quest with this classic algorithm, renowned for its simplicity and remarkable performance in text classification tasks. It's a formidable starting point for understanding sentiment analysis.
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Multinomial Bayes with TF-IDF and GridSearchCV: Prepare to be amazed as we combine the potent forces of Multinomial Bayes and TF-IDF (Term Frequency-Inverse Document Frequency), unleashing enhanced feature representation and uncovering profound insights. We enchance these 2 great methods with the ultimate weapon in hyperparameter tuning—GridSearchCV—elevating our sentiment analysis to new heights with its ability to unlock the optimal combination of parameters.
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🤗 Hugging Face DistilBERT: Brace yourself for an encounter with a true superstar of the NLP world. DistilBERT, born from the BERT (Bidirectional Encoder Representations from Transformers) family, takes sentiment analysis to unprecedented levels of accuracy and understanding. Get ready to be captivated by its ability to grasp the intricate context and dependencies within the text.
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If you have any questions, suggestions, or potential collaborations related to this project, I would love to hear from you. Feel free to connect with me on LinkedIn.
Thank you for exploring the Seoul Bike Share Dataset Project, and I hope you find the insights and models developed in this project valuable for optimizing bike sharing operations.
Enjoy your NLP expedition!
Best regards,
David Shields
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