Building in public. MTech DS student, 4 ML projects live, currently hunting an internship. Starting to document the journey here.
https://t.co/NVuCFzMo3S
Day 4 of building in public:
>Wrapped up the Streamlit frontend for my Spotify recommender
>Used Antigravity to build a proper UI for my demand elasticity project.
The difference in quality between the two is wild.
Never going back to default Streamlit ��
Day 3: Built the recommendation engine 🎧
Implemented content-based filtering using cosine similarity to find songs with similar audio “DNA”. Now the system can suggest tracks based on vibe, not just mood.
From clusters → real recommendations
#MachineLearning#DataScience