_

kuldeep.py

from education import ElectricalEngineering

class Kuldeep(MLEngineer, SoftwareDeveloper):

"""

Building ML systems end-to-end —

from raw data to deployed models

with real-world impact.

"""

def __init__(self):

self.role = "ML Engineer"

self.base = "Delhi, India"

self.exp = 0 # fresher

def mission(self) -> str:

return "From raw data to production-ready ML — end to end."

ML ENGINEER //
ETL & AI SYSTEMS //
OPEN TO OPPORTUNITIES

Programming Languages
Python C++ Java MATLAB SQL Data Structures & Algorithms
Machine Learning
PyTorch TensorFlow Scikit-learn XGBoost BERT NLP Neural Networks Supervised ML Unsupervised ML
ML Techniques
Recommendation Systems Time-Series Forecasting Feature Engineering Dimensionality Reduction
Data & Analytics
Pandas NumPy Matplotlib Seaborn Streamlit
Cloud & Backend
AWS EC2 S3 Lambda DynamoDB SQS Flask FastAPI
Tools & Databases
MongoDB Git GitHub Jupyter VS Code

~/Credit-Card-Fraud-Detection

view_source →
MLOps Fraud Detection SHAP / LIME

End-to-end MLOps project — hybrid ensemble model, Streamlit dashboard, SHAP/LIME explainability, and data drift detection.

~/Product-Recommendation-System

view_source →
Hybrid Recommender SVD MongoDB

Personalized Hybrid Recommender for games using SVD + TF-IDF + ensemble methods on 230K+ reviews with a live Streamlit dashboard.

~/Urban-Mobility-Data-Analysis

view_source →
Time Series Forecasting Geospatial

NYC Uber rides analysis — Time Series Forecasting with Prophet, Folium maps, and demand modeling using Pandas, NumPy, and Streamlit.

~/explore_all  →

// Interested in collaboration? Execute the command below.

> mailto:contact@kuldeepbhardwaj.me