The objective of this project is to gain insights into the traffic patterns and user behavior on an academic teaching notes website over a six-year period, from September 14, 2014, to August 19, 2020. It aims to explore trends, patterns, and relationships within the dataset to provide valuable insights into user engagement and traffic fluctuations. This project also aims to develop a model that forecast the website traffic.

Website

1. Notebook: This Jupyter Notebook is an essential part of the project dedicated to analyzing website traffic and developing a model for forecasting the website unique visitor.
2. Train Data: The training dataset was obtained from Kaggle, and the source link is provided above. This dataset serves as the foundation for analysis and model development.

1. Objectives
2. Importing Libraries
3. Data Collection
4. Preprocessing
5. Exploratory data Analysis
6. Feature Engineering
7. modeling
8. Model review

To make the most of this notebook and our analysis:

1. Clone this repository to your local machine.
2. Ensure you have the required Python libraries and dependencies installed.
3. Open the notebook in Jupyter Notebook or any compatible environment.
4. Execute each cell in the notebook sequentially to reproduce the analysis and model development.

The analysis is ongoing, and the notebook is continuously updated with new findings and model improvements.