# Hello, folks!
I'm Preet

About me:

🧑‍🎓 Currently Pursuing MS in Data Analytics Engineering at Northeastern Universiry, Boston
🕵 Business Intelligence Developer, Searce Inc.
🔭 Feel free to check out my latest Project
🌱 I’m currently learning Data Science & Machine learning🤩
💬 Problem Solver. Passion Catalyst. Change Maker. Love simulating conversations especially if done over beer. I 'm looking to collaborate to work on ML projects😎
📫 How to reach me 💁

⚡ Fun fact
1. Google uses about 1,000 computers to answer every single search query.
2. By 2025, the Data Science analytics sector in India is estimated to grow eightfold, reaching $16 billion.
3. Data Scientists and Data Analysts are NOT the Same
4. You do Not Need to be a Tech Savvy or Hold a PhD to Learn Data Science
5. Data Science is Not Just Excel Sheets
6. Data Science Competitions and Real Life Projects are Different
7. Data Science Field has Different Roles, Not just Data Scientists
8. Data Science Needs Great Communication Skills
9. Data Science is Not for Everyone
10. Less than 0.5% of all data we create is ever analysed and used.

⚙️ My GitHub Analytics

🏃 Happy Coding 🏃

Show ❤️ By Starring My

while(!(succeed=try()); )

Hey,Wait! 👋 don't foget to check out my social media handles 😎

⚡ Tab here :P 🎁

Ynpreet's Projects

best-readme-template

An awesome README template to jumpstart your projects!

content-based-movie-recommendation-system

Among the 3 types of recommendation engines, I have built a content-based recommendation engine using Python and Scikitlearn. I first understood basic concepts such as cosine distance, euclidean distance and when to use each of them. Finally, by using IMDB 5000 movie dataset built a content-based recommendation engine using CountVectorize and Cosine similarity scores between movies.