Hi I am Subhradip Halder. You can call me Halder or just Deep. Thanks for visiting my page.
NOW
π Iβm currently working as a Data Science/ Data Analysis freelancer.
π’ I'm currently staying in Kolkata,India.
β‘οΈ I am the father of www.zealousi.com - POD Ecommerce store.
BIO
βοΈ I use daily: python,SQL,Power BI/Tableau,ML Algos.
π I'm mostly active within the Data Science, NFT and Crypto Community
π
Designed and Devloped- www.zealousi.com - POD ( Print on Demand Ecommerce store in India.)
π± Currently Learning - GCP(Google Cloud) ML.
π¬ Ping me about Data Science, Data Analytics, Machine Learning NFT, Creative Design.
π« Email Me - subhradipmsm@gmail.com
β‘οΈ Fun fact: I'm a huge fan of Elon Musk,generative computer art.
PAST
π« Fintech Salesforce Consultant - Deloitte Consulting USA with 9 years of exp.
πππ πππ πππππ ππ ππ πππ πππππ ππ ππ’ ππππππ πππππππ. π΅πππππ ππ’ πππππππ!
This portfolio is a compilation of all my work which includes Data Science projects, Data Analysis projects, Data Visualization, NLP projects and much more.
Recommenders are systems, which predict ratings of users for items. There are several approaches to build such systems and one of them is Collaborative Filtering.
This notebook and app, shows a recommendation system where the user selects a movie from the list of top 5000 movies and it gives you the top 5 most similar movies along with their images.
This notebook is also deployed in Heroku , so you can use the app using this URL : https://similar-movies.herokuapp.com
This a machine learning project where the user enters a summary or description and the app directly predicts a genre fit for the summary, and then finds similar books based on the summary's closest cosine similarity score. The data for books were first scraped from goodreads and then the model was trained to predict the summary.