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mayank-gariya/README.md

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Portfolio

πŸ‘¨β€πŸ’Ό About Me

I'm a Data Scientist & Machine Learning Engineer dedicated to transforming raw data into actionable intelligence. I specialize in the complete ML lifecycle: from meticulous data preprocessing and exploratory analysis to sophisticated feature engineering, model training, rigorous evaluation, continuous optimization, and production deployment. My approach emphasizes iterative improvement until models achieve reliable, meaningful performance that drives real-world impact.

6 followers β€’ 4 following


πŸ› οΈ Tech Stack Mastery

πŸ”„ Data Preprocessing

Cleaning, transforming, and preparing data for analysis

Python Pandas NumPy Scikit-Learn

Jupyter SQL

πŸ“Š Data Visualization

Creating compelling visual narratives from complex data

Matplotlib Seaborn Plotly

PowerBI Tableau

πŸ€– Machine Learning

Building and optimizing models for predictive excellence

Scikit-Learn XGBoost LightGBM

TensorFlow PyTorch

πŸš€ Deployment & MLOps

Operationalizing models in production environments

Streamlit Gradio FastAPI

Docker AWS


🎯 Learning & Growth Focus

🧠 Advanced ML βš™οΈ MLOps πŸ€– LLM Engineering
Deep Learning Architectures Model Deployment Pipelines Prompt Engineering
Ensemble Methods Monitoring & Observability RAG Systems
Hyperparameter Optimization CI/CD Automation Fine-tuning LLMs
πŸ—οΈ AI System Design πŸ“Š Model Monitoring πŸ”¨ Feature Engineering
Scalable ML Systems Performance Tracking Domain Knowledge Integration
Architecture Patterns Drift Detection Feature Selection & Creation
System Optimization Alerting Frameworks Data-driven Insights

πŸ”— Connect With Me

LinkedIn Portfolio GitHub Email


πŸŽ“ What I Bring to the Table

  • βœ… End-to-End ML Solutions β€” From problem definition to production deployment
  • βœ… Data-Driven Decision Making β€” Extracting insights that matter
  • βœ… Scalable Systems β€” Building models that perform reliably at scale
  • βœ… Continuous Improvement β€” Iterative refinement for optimal results
  • βœ… Cross-functional Collaboration β€” Translating ML to business value
  • βœ… Production Excellence β€” Clean, maintainable, and deployable code

πŸ’‘ "Data is the raw material; ML is the refinery; insights are the fuel for growth."

Let's collaborate on data-driven projects and build intelligent systems together!

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  1. 9-days-challange 9-days-challange Public

    In this 10 day challange i will try to improve my basics of data science that is stats ,python and EDA + visualisation

    Jupyter Notebook 2

  2. SQL_projects SQL_projects Public

    1

  3. working-with-apis working-with-apis Public

    Jupyter Notebook 1

  4. asking-great-question-series asking-great-question-series Public

    Jupyter Notebook

  5. projects projects Public

    Jupyter Notebook 2