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ddkryptonite/README.md

💫 About Me:

I'm currently working on various data analysis and machine learning projects touching our everyday lives.
Looking forward to diving deep into big data technologies.

💻 Tech Stack:

Python scikit-learn MicrosoftSQLServer Power Bi Pandas GithubPages MicrosoftSQLServer MySQL Postgres SQLite Adobe After Effects Canva NumPy Plotly Scipy GitHub Portfolio

📊 GitHub Stats:



🏆 GitHub Trophies

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  1. Power-BI-Analysis-Automobil-Dataset Power-BI-Analysis-Automobil-Dataset Public

    A Power BI project report for the automobil dataset for Fuel consumption

    1

  2. Financial-Analysis-Prediction Financial-Analysis-Prediction Public

    PharmaCrest is a pharmaceutical manufacturing company producing vaccines, OTC drugs, and prescription medications. This project focuses on analyzing financial KPIs, exploring trends in revenue and …

    Jupyter Notebook 1

  3. Credit-Scoring-for-Financial-Inclusion-Unbanked- Credit-Scoring-for-Financial-Inclusion-Unbanked- Public

    A machine learning project that builds a credit scoring model using alternative data sources (such as mobile usage and transactional data) to assess the creditworthiness of individuals without trad…

    Jupyter Notebook 1

  4. Semi-arid-Farming-Analysis Semi-arid-Farming-Analysis Public

    Data analysis and visualization of rainwater harvesting's impact on crop yield, water usage, and profitability in semi-arid regions. This project evaluates the effectiveness of rainwater harvesting…

    Jupyter Notebook

  5. Social-Media-Video-Engagement-Analysis Social-Media-Video-Engagement-Analysis Public

    This project focuses on analyzing the engagement of trending social media videos from May to August 2021. The dataset includes metrics such as likes, shares, comments, plays, and video length, with…

    Jupyter Notebook

  6. Telecommunications-Customer-Segmentation-KNN-Classifier Telecommunications-Customer-Segmentation-KNN-Classifier Public

    This project aims to classify customers of a telecommunications provider into four predefined service usage groups using demographic data. By predicting group membership,using KNN, the company can …

    Jupyter Notebook