I'm a self-taught Python coder with a diverse skill set in Data Science and AI, currently working as a Software Development Engineer I at Sidetrek, a US-based AI startup. My passion lies in becoming a data scientist who seeks to play a pivotal role in transforming data into actionable insights and contributing to AI research within the organization, drawing upon my technical expertise, entrepreneurial background, and innovative mindset.

• Language:
  • Python
  • SQL
  • R
• Machine Learning:
  • Classification, Regression, Clustering, Time-series Forecasting, Anomaly Detection, Recommender Engine
  • Libraries:
    • Scikit-learn,
    • XGBoost,
    • Catboost,
    • LightGBM,
    • PyCaret,
    • Prophet,
    • ARIMA & SARIMA
• Feature Engineering: Feature scaling, feature encoding, binning or discretization, feature extraction, etc.
• Data Preprocessing: Data cleaning, data imputation, normalization, and transformation skills using libraries like Pandas, Scikit-learn, etc.
• Model Evaluation & Improvement: Model evaluation through cross-validation, metrics (e.g., accuracy, F1 score), and ROC curves, and hyperparameter tuning using GridSearchCV, RandomizedSearchCV and Bayesian optimization (using Optuna)
• Model Interpretability: Explaining models using XAI tools like SHAP, Facets and LIME.
• Natural Language Processing (NLP):
  • Libraries:
    • SpaCy
    • NLTK
    • Hugging Face Transformers
• Computer Vision:
  • Libraries:
    • OpenCV
    • YOLO
• Data Versioning: Data version control using DVC
• Model Management: Experiment tracking and model versioning using MLFlow
• Model Deployment: Containerization using Docker, creating web apps using Flask, Streamlit, deploying models as REST APIs using FastAPI, BentoML, etc.
• Neural Network:
  • ANN, CNN, RNN, LSTM
  • Libraries:
    • PyTorch
• BI Tools:
  • Tableau

• I'm a 3x Kaggle Expert. Visit my Kaggle Profile

• I post Data Science and ML related writeups on my Medium blog.

• 📮 [email protected]