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arvindd333/README.md

Hi, I'm Arvind

AI / ML and Data Analytics enthusiast with a Master's degree in Information Technology and 3+ years of experience in data analysis and operational reporting at Flipkart. I enjoy working with data to extract insights, build machine learning models, and develop practical AI solutions.

🔍 My interests include Machine Learning, Natural Language Processing (NLP), Data Analytics, and Generative AI. I have hands-on experience with Python, SQL, Power BI, and data analysis libraries such as Pandas and NumPy.

💡 Through my internship and projects, I have worked on data preprocessing, exploratory data analysis, machine learning fundamentals, and building analytics dashboards.

Technical Skills

  • Programming: Python, SQL
  • Machine Learning: Scikit-learn, PyTorch (Basics), NLP
  • Data Analysis: Pandas, NumPy, Exploratory Data Analysis
  • Visualization: Power BI, Advanced Excel
  • Tools: Git, GitHub, Jupyter Notebook

Featured Projects

  • NLP Intent Classification System
  • Customer Segmentation using Machine Learning
  • Sales Data Analytics Dashboard (SQL + Power BI)

Certifications

  • Generative AI Foundations – upGrad × Microsoft
  • Basic Python Programming – upGrad
  • Data Processing & Business Analytics – Anudip Foundation

Currently Learning

  • Deep Learning fundamentals
  • Model deployment for AI applications
  • Advanced machine learning workflows

📫 Connect with me: LinkedIn: https://linkedin.com/in/arvind-dyavanapelli

Pinned Loading

  1. Retail-Sales-Performance-Analysis Retail-Sales-Performance-Analysis Public

    End-to-end Retail Sales Performance Analysis using Python, Pandas, Matplotlib, Seaborn, and Google Looker Studio.

    Jupyter Notebook

  2. Crypto-Market-Analysis Crypto-Market-Analysis Public

    End-to-end Cryptocurrency Market Analysis using CoinGecko API, Python, Pandas, NumPy, Feature Engineering, EDA, and Data Visualization.

    Jupyter Notebook

  3. telecom-customer-churn-analysis telecom-customer-churn-analysis Public

    End-to-end Telecom Customer Churn Analysis and Prediction using Python, EDA, Feature Engineering, and Machine Learning.

    Jupyter Notebook