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anurag-ds/README.md

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๐Ÿงฌ whoami

class Anurag:
    def __init__(self):
        self.role = "Aspiring ML Engineer"
        self.location = "Lucknow, India ๐Ÿ‡ฎ๐Ÿ‡ณ"
        self.languages = ["Python", "C++"]
        self.currently_learning = "Machine Learning & Deep Learning"
        self.fun_fact = "I debug faster than I explain what I'm debugging"

    def say_hi(self):
        print("Thanks for stopping by โ€” let's build something! ๐Ÿš€")

me = Anurag()
me.say_hi()

๐Ÿ› ๏ธ Tech Arsenal


๐Ÿ Languages

  • Python
  • C++

๐Ÿ“Š Data & ML

  • Pandas ยท NumPy
  • scikit-learn
  • Matplotlib

โš™๏ธ Tools

  • Git & GitHub
  • VS Code ยท Jupyter
  • LeetCode

๐Ÿš€ Featured Builds

๐ŸŒธ Iris Classifier

Machine Learning model to classify iris flowers using a Random Forest algorithm.

๐Ÿ“š Amazon Bestselling Books Analysis

Exploratory data analysis on Amazon's Top 50 bestselling books (2009โ€“2019).

๐Ÿ“Š Book Genre Rating Analysis

Comparison of Fiction vs Non-Fiction average reader ratings.

๐Ÿ”— Add a direct link to each project's repo here once you share the exact repo URLs โ€” happy to wire them in.

๐Ÿ“Š The Numbers Game

๐Ÿ“ˆ Contribution Snake

๐Ÿ’ญ Random Dev Wisdom

๐Ÿ“ซ Let's Connect

LinkedIn Gmail

โญ๏ธ "Growing with every line of code."


โญ๏ธ "Growing with every line of code."

Popular repositories Loading

  1. Amazon-Bestselling-Books-Analysis Amazon-Bestselling-Books-Analysis Public

    Exploratory Data Analysis of Amazonโ€™s Top 50 Bestselling Books (2009โ€“2019) using Python, Pandas, and Matplotlib.

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  2. iris-ml-classifier iris-ml-classifier Public

    Random Forest classifier on Iris dataset

    Jupyter Notebook 1

  3. Restaurant-Market-Analysis Restaurant-Market-Analysis Public

    Exploratory data analysis (EDA) on restaurant data to examine pricing trends, customer ratings, and operational performance.

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  4. dsa-solution dsa-solution Public

    Daily DSA Practise in C++

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  5. dengue-early-warning-system dengue-early-warning-system Public

    Predicts dengue outbreak risk 1 month ahead for Indian districts by combining IDSP epidemiological data with weather data (rainfall, temperature). Random Forest model + live Streamlit dashboard.

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  6. titanic-missing-values-analysis titanic-missing-values-analysis Public

    A data cleaning and EDA project on the Titanic dataset โ€” handles missing values in Age, Cabin, and Embarked, and analyzes survival trends by demographics.

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