Academic-Projects

Academic Projects

This repository contains various academic projects, including a Bot IoT project for dataset analysis and model development, a Number Guessing Game, and a Hilwitz Portfolio showcasing personal skills and projects.

Table of Contents

1. Bot IoT: IoT Bot Dataset Analysis and Model Development
2. Number Guessing Game
3. Hilwitz Portfolio
4. How to Run

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Bot IoT: IoT Bot Dataset Analysis and Model Development

This project involves working with the IoT Bot Dataset from Kaggle. It includes tasks like data observation, cleaning, encoding of categorical variables, and feature scaling. The project uses Python and its data science libraries to visualize, process, and split the data, followed by training and evaluating a machine learning model to predict outcomes based on the dataset.

Files:

• bot_iot.ipynb: A Jupyter Notebook containing the code for data preprocessing, feature engineering, model training, and evaluation.
• requirements.txt: The list of Python dependencies required for this project.

Role:

• Data preprocessing
• Model training using machine learning algorithms
• Model evaluation

Technologies Used:

• Python
• Pandas
• Scikit-learn
• Matplotlib
• Seaborn

How to Run:

1. Clone or download the repository.

2. Install the required dependencies using the following command:

   pip install -r requirements.txt

3. Open bot_iot.ipynb in Jupyter Notebook.

4. Run the notebook step-by-step to observe data, preprocess it, train a model, and evaluate its performance.

Number Guessing Game This is a simple Python-based number guessing game where the user has to guess a randomly generated number within a certain range. The game gives feedback if the guess is too high or too low, and the user wins once they guess the correct number.

Files: actualcode.py: The Python script for the number guessing game.

How to Run: Make sure you have Python installed.

Run the following command in your terminal or command prompt:

bash Copy Edit python actualcode.py Follow the instructions in the terminal to play the game.

Hilwitz Portfolio This is a simple frontend portfolio showcasing your skills, projects, and contact details. It is built using HTML, CSS, and JavaScript.

Files: index.html: The main HTML file for the portfolio.

style.css: The CSS file for styling the portfolio.

script.js: The JavaScript file for interactive functionality.

How to Run on Live Server (using VS Code): Clone or download the repository.

Open the hilwitz_portfolio folder in Visual Studio Code.

Make sure you have the Live Server extension installed in VS Code.

Right-click on the index.html file and select "Open with Live Server".

The portfolio will open in your default web browser, and you will be able to see your Hilwitz Portfolio live.

How to Run

1. Running the Bot IoT Project: Open the bot_iot.ipynb file in Jupyter Notebook.

Install any necessary libraries using: pip install -r requirements.txt Follow the steps in the notebook for data processing, model training, and evaluation.

2. Running the Number Guessing Game: Open the actualcode.py file in VS Code or your preferred text editor.

Run the Python script in the terminal: python actualcode.py 3. Running the Hilwitz Portfolio: Open the hilwitz_portfolio folder in VS Code.

Right-click on index.html and choose "Open with Live Server" to view the portfolio in the browser.