src/lib/data.ts

export type Project = {
  id: number;
  title: string;
  description: string;
  methodologies: string[];
  outcomes: string;
  githubUrl: string;
};

export const aboutMe = {
  name: "Sameer Banchhor",
  title: "Aspiring Data Scientist",
  bio: "I am a passionate and driven data scientist in training, with a strong foundation in machine learning, statistical analysis, and data visualization. My journey is fueled by a curiosity to uncover hidden patterns in data and translate them into actionable insights. Through my projects, I've honed my skills in predictive modeling, natural language processing, and time series analysis. I am eager to apply my analytical mindset and technical abilities to solve complex, real-world problems and contribute to a data-driven organization.",
};

export const projectDescriptions = [
  "Developed a machine learning model to predict customer churn for a subscription-based service. The project involved data preprocessing, feature engineering, and the implementation of logistic regression and random forest models to identify key factors driving churn. The model achieved an accuracy of 85%, providing actionable insights for customer retention strategies.",
  "Created a real-time sentiment analysis dashboard using Python, Flask, and Plotly. The application fetches live data from social media APIs, processes the text to determine sentiment (positive, negative, neutral) using VADER, and visualizes the results in an interactive web interface. This tool can be used for brand monitoring and market research.",
];

export const projects: Project[] = [
  {
    id: 1,
    title: "Customer Churn Prediction",
    description: projectDescriptions[0],
    methodologies: [
      "Logistic Regression",
      "Random Forest",
      "Feature Engineering",
      "Scikit-learn",
      "Pandas",
    ],
    outcomes:
      "Achieved 85% accuracy in predicting churn, enabling targeted retention campaigns.",
    githubUrl: "https://github.com/sameerbanchhor-git",
  },
  {
    id: 2,
    title: "Real-Time Sentiment Analysis Dashboard",
    description: projectDescriptions[1],
    methodologies: [
      "VADER Sentiment",
      "Social Media API",
      "Plotly Dash",
      "NLP",
    ],
    outcomes:
      "Developed a tool for real-time brand monitoring and market analysis.",
    githubUrl: "https://github.com/sameerbanchhor-git",
  },
];