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AI Hackathon Winner - Machine Learning, EDA & Chatbot Development with LLM Training

Overview

This repository contains the code, problem sets, and results from the AI Hackathon in which I won first place. The hackathon consisted of two tasks:

  • Task 1: Machine Learning and Exploratory Data Analysis (EDA)
  • Task 2: Chatbot Development with LLM Training

Task 1: Machine Learning & EDA

In the first task, I tackled a machine learning problem that required developing a model to achieve the highest accuracy. The task included:

  • Data Preprocessing: Handling missing values, feature scaling, and encoding categorical variables.
  • Exploratory Data Analysis (EDA): Conducting in-depth analysis to uncover patterns, correlations, and insights within the data.
  • Model Selection: Experimenting with various machine learning algorithms and fine-tuning hyperparameters to optimize model performance.
  • Evaluation: Using metrics like accuracy, precision, recall, and F1-score to assess model performance.

Task 2: Chatbot Development with LLM Training

The second task involved building an intelligent chatbot capable of understanding and responding to user queries effectively. The development process included:

  • LLM Training: The chatbot was trained on provided PDFs using a large language model (LLM) to enhance its knowledge base and improve its response accuracy.
  • Intent Recognition: Leveraging natural language processing (NLP) techniques to identify user intents.
  • Dialog Management: Creating a flow to manage conversations seamlessly.
  • Deployment: Implementing the chatbot to interact with users in a real-time environment.

Getting Started

To explore the code and run the notebooks:

  1. Clone the repository:
    git clone https://github.com/yourusername/ai-hackathon-winner.git
  2. Navigate to the project directory:
    cd ai-hackathon-winner
  3. Install the required dependencies:
    pip install -r requirements.txt
  4. Run the Jupyter notebooks or scripts as needed.

Results

  • Task 1: Achieved the highest accuracy in the machine learning challenge.
  • Task 2: Developed a chatbot with the best performance metrics, significantly enhanced by LLM training.

Acknowledgments

Special thanks to the hackathon organizers and my team for their support and collaboration.

Contact

Feel free to reach out if you have any questions or suggestions.

About

This repository contains the problem sets, code, and results from an AI Hackathon where I secured the top position. The hackathon involved two key tasks: Task 1 focused on machine learning and exploratory data analysis (EDA), while Task 2 involved building a chatbot.

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