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dasrajdeep346-tech/README.md

Rajdeep Das

📊 Data Science  ·  🤖 Machine Learning  ·  📈 Analytics

Turning raw data into decisions.

Email GitHub Kaggle

Followers Focus Location Open to


👋 About Me

class RajdeepDas:
    def __init__(self):
        self.role     = "Data Science / Machine Learning Student"
        self.focus    = ["Predictive Modeling", "Survival Analysis", "EDA"]
        self.stack    = ["Python", "pandas", "scikit-learn", "SQL"]
        self.learning = ["Deep Learning", "MLOps", "Feature Engineering"]

    def current_goal(self):
        return "Build end-to-end ML projects that solve real problems"
  • 🔬 I build machine learning projects that turn messy, real-world datasets into models people can act on.
  • 📊 Comfortable across the full pipeline — EDA → preprocessing → modeling → evaluation → interpretation.
  • 🧠 Currently deepening my work in healthcare analytics and classification modeling.
  • 📫 Reach me at dasrajdeep346@gmail.com

🛠️ Tech Stack

Languages & Core

Python SQL Git Markdown

Data Science & Machine Learning

pandas NumPy scikit-learn SciPy LightGBM lifelines

Visualization & Environment

Matplotlib Seaborn Jupyter Colab VS Code


🚀 Featured Projects

🎗️ Breast Cancer Risk Prediction

Predicts 10-year mortality in breast cancer patients by combining survival analysis with supervised classification.

Kaplan-Meier Cox PH Logistic Regression SVM Decision Tree

2,509 patients · 34 features · best accuracy 99.60%

➡️ View project

💼 Employee Retention Prediction

Predicts whether a data scientist is likely to seek a job change, built on HR Analytics data.

LightGBM Classification Feature Engineering

19,158 records · ROC-AUC 0.807

➡️ View project

🧪 What I Work On

Area What that looks like in practice
🔍 Exploratory Data Analysis Distribution profiling, correlation heatmaps, missing-value strategy, outlier handling
🧹 Data Preprocessing Imputation, encoding, scaling, deduplication, leakage checks
🤖 Predictive Modeling Logistic Regression, SVM, Decision Trees, LightGBM, model comparison
📉 Survival Analysis Kaplan-Meier estimation, Cox Proportional Hazards, hazard ratios
📊 Evaluation & Interpretation ROC-AUC, precision/recall, confusion matrices, feature importance

🌱 Currently Learning

Area Focus
🧠 Deep Learning Neural networks, TensorFlow / PyTorch fundamentals
⚙️ MLOps Model deployment, versioning, reproducible pipelines
🗄️ SQL & Data Engineering Query optimization, warehousing, ETL
📈 Advanced Statistics Causal inference, experiment design, Bayesian methods

🤝 Let's Connect

I'm open to collaboration on data science projects, research, and internship opportunities.

Contact



"Without data, you're just another person with an opinion."
— W. Edwards Deming



Pinned Loading

  1. breast-cancer-risk-prediction breast-cancer-risk-prediction Public

    Survival analysis and ML models predicting 10-year mortality in breast cancer patients (Kaplan-Meier, Cox PH, Logistic Regression, SVM, Decision Tree)

  2. employee-retention-prediction employee-retention-prediction Public

    Machine learning classification model predicting whether a data scientist is likely to seek a job change. LightGBM, ROC-AUC 0.807, HR Analytics dataset (19,158 records).

    Jupyter Notebook

  3. fraud-detection-analysis fraud-detection-analysis Public

    End-to-end fraud detection on mobile-money transactions — leakage-free scikit-learn pipeline, six hypothesis tests, and a 3-model comparison (Random Forest: 0.9982 F1, 0.9999 PR-AUC).