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Track your workouts with Natural Language

Track your workouts with Natural Language

View Live Project

About the project.

Ditch the dropdowns. Just write your workout and let NLP do the rest. 

Natural Language Processing (NLP) is a multidisciplinary field that combines computer science, linguistics, and machine learning. Its primary goal is to enable computers to understand and process human language in a natural and efficient manner.

Project Type

  • AI

  • Machine Learning

  • APIs / Microservices

  • Data Science & Engineering

Tech Stack / Toolbox

  • Python

  • NumPy

  • Pandas

  • scikit-learn

My Role

My Role: NLP Developer & Machine Learning Engineer
In this project, I:

  • Designed and developed an NLP-powered workout tracker that interprets free-text input instead of dropdowns.

  • Built text preprocessing pipelines (tokenization, stemming, lemmatization, stop-word removal) using Python libraries such as NLTK, spaCy, and scikit-learn.

  • Applied classification and entity recognition models to extract structured data (exercises, reps, weights) from natural language.

  • Implemented sentiment and intent analysis to improve workout recommendations and personalization.

  • Leveraged Jupyter Notebooks for experimentation and iterative model development.

  • Deployed the solution as a demo, showcasing practical NLP applications beyond traditional text analytics.

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