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shubhamtyagi1306/README.md

Hi there, I'm Shubham Tyagi 👋

I am a passionate data analyst and data scientist enthusiast with a strong interest in uncovering insights from data, building predictive models, and solving complex problems. Welcome to my GitHub profile!

🚀 About Me

  • 🌱 I’m currently learning Machine Learning and Deep Learning
  • 👯 I’m looking to collaborate on data science projects
  • 🤔 I’m looking for help with advanced machine learning techniques
  • 💬 Ask me about Python, Data Analysis, Machine Learning, and Visualization
  • 📫 How to reach me: shubhamtyagi1306@gmail.com
  • ⚡ Fun fact: I love playing chess and solving puzzles

🛠️ Skills & Tools

  • Programming Languages: Python
  • Data Analysis: Pandas, NumPy
  • Data Visualization: Matplotlib, Seaborn
  • Machine Learning: Scikit-Learn
  • Big Data Technologies: Hadoop, Spark
  • Tools: Jupyter Notebook, Google Colab, Git

📫 Connect with Me

🔥 My Projects

  • Iris-Insights-A-NumPy-Analysis) - Built a data analysis pipeline, performed statistical computations, and derived insights using Python and NumPy. Implemented normalization, correlation analysis, and linear algebra computations.
  • Online-Retail-Store-Analysis-using-Pandas ) - Developed an end-to-end data analysis project using the Pandas library on a customer transactions dataset, including data cleaning, exploratory analysis, and insights generation.

Thank you for visiting my profile! Feel free to reach out if you want to collaborate or just chat about data science and analytics.

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  1. Loan-Approval-Prediction-Using-Decision-Trees Loan-Approval-Prediction-Using-Decision-Trees Public

    This project applies the Decision Tree algorithm to predict whether a loan application will be approved based on various applicant details. It helps financial institutions automate the loan approva…

    Jupyter Notebook

  2. Customer-Segmentation-Using-K-Means-Clustering Customer-Segmentation-Using-K-Means-Clustering Public

    This project applies K-Means Clustering, an unsupervised machine learning algorithm, to segment mall customers based on their Annual Income and Spending Score. The goal is to identify distinct cust…

    Jupyter Notebook

  3. Loan_Amount_Prediction_Linear_Regression Loan_Amount_Prediction_Linear_Regression Public

    This project aims to predict a customer's loan amount based on their annual income using Simple Linear Regression and enhanced techniques like Ridge, Lasso, and Bayesian Optimization.

    Jupyter Notebook

  4. Employee-Attrition-Prediction-using-Logistic-Regression Employee-Attrition-Prediction-using-Logistic-Regression Public

    This project aims to predict whether an employee is likely to leave the organization using Logistic Regression with L1/L2 regularization and hyperparameter tuning techniques. It uses the IBM HR Ana…

    Jupyter Notebook

  5. Customer-Segmentation-using-knn Customer-Segmentation-using-knn Public

    This project uses the K-Nearest Neighbors (KNN) algorithm to classify customers into segments based on their demographics and spending behavior. We go through building a base model, performing hype…

    Jupyter Notebook

  6. SMS-Spam-Detection-using-Naive-Bayes SMS-Spam-Detection-using-Naive-Bayes Public

    With the increasing volume of unsolicited messages, spam detection has become a crucial task in communication systems. The goal is to create an intelligent classifier that can predict whether an in…

    Jupyter Notebook