Python for Machine Learning

Welcome to the Python for ML repository! This repository provides a comprehensive set of resources, code examples, and learning materials to help you get started with Python. It covers a range of topics from basic fundamental to data visualization, web scraping, and building interactive web applications.

---

📑 Table of Contents

1. Introduction
2. Installation
3. Usage
4. Learning Resources
5. License

---

📘 Introduction

This repository contains Python scripts and Jupyter notebooks that demonstrate various data science and machine learning techniques using widely used libraries.

Technologies covered include:

• NumPy: For numerical operations and working with arrays ➗
• Pandas: For data manipulation and analysis 🐼
• Matplotlib & Seaborn: For data visualization 📊
• BeautifulSoup (bs4): For web scraping 🕸️
• Flask: For building web applications and APIs 🌐
• Streamlit: For building interactive web apps for data science ⚡

Each module focuses on a specific concept or technique, offering code examples and explanations.

---

⚙️ Installation

Before you can use the scripts and notebooks, ensure you have Python 3.x installed. Follow the steps below to set up the environment:

Step 1: Clone the Repository

First, clone this repository to your local machine:

git clone https://github.com/Abhinavks1405/Python-for-ML.git

Step 2: Navigate to the Project Directory

After cloning the repository, navigate to the project directory:

cd Python-for-ML

Step 3: Create a Virtual Environment

To avoid package conflicts, you can create a virtual environment using the following command:

python -m venv venv

Activate

On Linux/macOS:

source venv/bin/activate

On Windows:

venv\Scripts\activate

Step 4: Install Required Packages

Install the necessary dependencies from the requirements.txt file:

pip install -r requirements.txt

📚 Learning Resources

Here are some additional resources that you may find useful for expanding your knowledge:

• NumPy Documentation: https://numpy.org/doc/
• Pandas Documentation: https://pandas.pydata.org/pandas-docs/stable/
• Matplotlib Guide: https://matplotlib.org/stable/contents.html
• Seaborn Tutorials: https://seaborn.pydata.org/tutorial.html
• BeautifulSoup Documentation: https://www.crummy.com/software/BeautifulSoup/bs4/doc/
• Flask Documentation: https://flask.palletsprojects.com/en/latest/
• Streamlit Documentation: https://docs.streamlit.io/

License

This repository is licensed under the MIT License. See the LICENSE file for details.