This repository contains various resources and code for learning and implementing Time Series Analysis techniques.

• 1. Introduction Time Series - Materials and code for an introduction to Time Series Analysis.
• 2. Smoothing - Techniques and methods for smoothing time series data.
• 3. Regression models - Code and explanations for implementing regression models in time series.
• 4. Tree models - Resources for tree-based models used in time series analysis.
• 5. Into to Anomaly Detection - Introduction to anomaly detection in time series data.
• Solutions/2. Smoothing - Solutions for the exercises and problems related to smoothing techniques.
• mymodule.py - A Python module containing useful functions for time series analysis.

1. Clone the repository:

   git clone https://github.com/HuseynA28/your-repo-name.git
   cd your-repo-name

2. Install the required packages:

   Ensure you have pip installed. Then, run:

   pip install -r requirements.txt

3. Run the code:

   You can navigate to any directory and run the Python scripts. For example:

   cd "1. Introduction Time Series"
   python script_name.py

Feel free to fork this repository and submit pull requests. For major changes, please open an issue first to discuss what you would like to change.

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