About the project.
Ditch the dropdowns. Just write your workout and let NLP do the rest.
Project Type
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AI
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Machine Learning
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APIs / Microservices
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Data Science & Engineering
Tech Stack / Toolbox
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Python
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NumPy
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Pandas
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scikit-learn
My Role
NLP Developer & Machine Learning Engineer
In this project, I:
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Designed and developed an NLP-powered workout tracker that interprets free-text input instead of dropdowns.
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Built text preprocessing pipelines (tokenization, stemming, lemmatization, stop-word removal) using Python libraries such as NLTK, spaCy, and scikit-learn.
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Applied classification and entity recognition models to extract structured data (exercises, reps, weights) from natural language.
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Implemented sentiment and intent analysis to improve workout recommendations and personalization.
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Leveraged Jupyter Notebooks for experimentation and iterative model development.
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Deployed the solution as a demo, showcasing practical NLP applications beyond traditional text analytics.
