Welcome to this repository, which serves as a comprehensive guide for coding in Python. This repository is structured to facilitate both beginners and intermediate learners in their journey to understand and apply Python in various domains, especially in data science and machine learning.
- Get started with Python: Understand the syntax, basic structures like lists, dictionaries, and loops.
- Functions and modules: Learn how to write reusable code using functions and how to organize your code with modules.
- Explore libraries like Matplotlib and Seaborn to create compelling data visualizations.
- Learn how to plot different types of data and customize your plots for presentations and reports.
- Dive deeper into Python with advanced topics like decorators, class inheritance, and more.
- Understand error and exceptions handling to write robust code.
- Introduction to Pandas for data manipulation and analysis.
- Get hands-on experience with PyTorch, a leading machine learning library.
- Implement basic machine learning algorithms and learn to handle real-world data.
- Learn how NumPy enhances performance with its powerful array operations.
- Perform complex numerical computations and manipulate large datasets efficiently.
- Understand the fundamentals of Markov Chains for probabilistic modelling and simulations.
- Apply Markov Chains in real-life scenarios and data-driven applications.
- Put your learning to the test with a series of exercises ranging from basic Python problems to complex algorithmic challenges.
- Solutions are provided for each exercise to help you validate your solutions and understand different approaches.
To get started, clone this repository to your local machine and navigate through the directories, which are organized by topics. Each directory contains Python scripts, Jupyter Notebooks, and markdown files with explanations and resources.
Happy Learning!