RS--FinalYear-Fitness-Freaks

Final Year machine learning project for fitness freaks

Completing theoritical part in review PPT. a. Literature Survey b. Referentials
Deciding user attributes.
Creating diagrams using draw.io.
Creating automated dataset using python scripts.
Creating collaborative filtering model using Machine learning algorithms + Jeremy Howard Recommendation system Technique using deep learning.
Saving the models and also transformers
Deploying the model in reactjs + Django based framework.

Name		Name	Last commit message	Last commit date
Latest commit History 20 Commits
.ipynb_checkpoints		.ipynb_checkpoints
Building Recommendation Engine Using Cosine Similarity Matrix and Haversine.ipynb		Building Recommendation Engine Using Cosine Similarity Matrix and Haversine.ipynb
Data Preparation 1 - Name and Gender.ipynb		Data Preparation 1 - Name and Gender.ipynb
Data Preparation 2 - DOB, Locality.ipynb		Data Preparation 2 - DOB, Locality.ipynb
Data Preparation 3 pre Normalisation.ipynb		Data Preparation 3 pre Normalisation.ipynb
FINAL - FITBUDDY.ipynb		FINAL - FITBUDDY.ipynb
Final Dataset before Normalisation.csv		Final Dataset before Normalisation.csv
Final Name - Gender - Location.csv		Final Name - Gender - Location.csv
Hybrid Recommendation.py		Hybrid Recommendation.py
Name Sheet With Gender.csv		Name Sheet With Gender.csv
Project Review 1.pptx		Project Review 1.pptx
README.md		README.md
Register.py		Register.py
locations Prajwal.csv		locations Prajwal.csv
locations.csv		locations.csv
preparation.txt		preparation.txt

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