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  • Tech Mahindra
  • Hyderabad

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padmasaivayigandla/README.md

Hi, I’m Padma Sai 👋

Aspiring Data Analyst / Data Scientist with hands-on experience in Python, SQL, Machine Learning, and Power BI.
I enjoy turning raw data into meaningful insights and building data-driven solutions for real-world business problems.

What I Do

  • Data Analysis & Exploratory Data Analysis (EDA)
  • Machine Learning
  • SQL Analytics & Business Queries
  • Dashboarding & Storytelling using Power BI
  • Python (Pandas, NumPy, Matplotlib, Seaborn)

Featured Projects

  • Lead Scoring using Logistic Regression
    Built a predictive model to identify high-potential sales leads and improve conversion rates.

  • Credit Risk Analysis (EDA)
    Analyzed consumer finance data to identify key drivers of loan default.

  • Movie Ratings Analysis using SQL
    Performed complex SQL analytics to derive insights on genres, ratings, actors, and production houses.

  • Home Loan Analysis using Power BI
    Designed an interactive dashboard to analyze loan applications, sanctions, and recovery trends.

  • Uber Traffic Prediction
    Built a time-based predictive model to forecast traffic volume at road junctions.

Tech Stack

Languages & Tools:
Python · SQL · Power BI · Excel · Git · Jupyter Notebook

Machine Learning: Classification Models, Model Evaluation

Libraries:
Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn

Certifications

  • Professional Certificate Program in AI and Data Science – UpGrad
  • Generative AI for Data science and AI Practitioners - Microsoft + UpGrad
  • Certificate of recognition: Data Science Internship - Uber
  • AI White belt - Tech Mahindra
  • Python for Data Science - Udemy

Currently Learning

  • Advanced Machine Learning techniques
  • Model deployment & business-focused analytics

Let’s Connect

--

⭐ Feel free to explore my repositories and reach out if you'd like to collaborate!

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  1. Uber-Predictive-traffic-modelling Uber-Predictive-traffic-modelling Public

    Develop a predictive model to accurately forecast hourly traffic volumes at different road junctions based on historical traffic data.

    HTML 1

  2. customer-segmentation-kmeans-clustering customer-segmentation-kmeans-clustering Public

    Customer segmentation using K-Means clustering on retail transaction data to identify distinct purchasing behaviors and support targeted marketing strategies.

    Jupyter Notebook

  3. lead-scoring-logistic-regression lead-scoring-logistic-regression Public

    Machine learning project using logistic regression to score and prioritize sales leads based on conversion probability, helping improve lead-to-sale conversion efficiency.

    Jupyter Notebook 1

  4. Regression-Case-Studies Regression-Case-Studies Public

    Collection of regression-based case studies using Python, covering simple, multiple, and feature-selected regression techniques on real-world datasets.

    Jupyter Notebook

  5. movie-ratings-analysis-sql movie-ratings-analysis-sql Public

    SQL-based analysis of movie ratings data to derive business insights for a global film release strategy.

    1

  6. home-loan-analysis-powerbi home-loan-analysis-powerbi Public

    Power BI dashboard analyzing home loan applications, sanctions, and recovery performance using customer, branch, product, and channel data.

    1