DL-Simplified Time Series Model on Counter Strike Market Sale Dataset

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : Time Series Model on Counter Strike Market Sale Dataset :red_circle: Aim : To develop a time series model based on the counter strike market sale dataset :red_circle: Dataset : https://www.kaggle.com/datasets/kieranpoc/counter-strike-market-sale-data :red_circle: Approach : Planning to test 3 time series model on this dataset

Auto-Regressive Integrated Moving Average (ARIMA)
Seasonal Auto-Regressive Integrated Moving Average (SARIMA)
Auto Regressive (AR)

📍 Follow the Guidelines to Contribute in the Project :

You need to create a separate folder named as the Project Title.
Inside that folder, there will be four main components.
- Images - To store the required images.
- Dataset - To store the dataset or, information/source about the dataset.
- Model - To store the machine learning model you've created using the dataset.
- requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

:red_circle::yellow_circle: Points to Note :

The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
"Issue Title" and "PR Title should be the same. Include issue number along with it.
Follow Contributing Guidelines & Code of Conduct before start Contributing.

:white_check_mark: To be Mentioned while taking the issue :

Full name : Arpit Sengar
GitHub Profile Link : arpy8
Email ID : [email protected]
Approach for this Project : Planning to test 3 time series model on this dataset
- Auto-Regressive Integrated Moving Average (ARIMA)
- Seasonal Auto-Regressive Integrated Moving Average (SARIMA)
- Auto Regressive (AR)
What is your participant role? GSSOC