Playbook: R Data Science Tutorial## OverviewCreate a data science tutorial using an R markdown notebook.## What’s Needed From User- Link to a dataset (csv file attachment or kaggle link)- Specific task to create a data science tutorial for## Procedure1. Download the dataset provided by the user.- If needed, download the dataset using the Kaggle CLI - you don't need any credentials for this2. Create an R markdown notebook titled `data_science_tutorial.Rmd`.3. Create a `tmp.Rmd` file for writing and saving intermediate code.4. Create 5 main sections inside the `data_science_tutorial.Rmd` file and add code from the `tmp.Rmd` file containing the following:- Dataset Statistics. Generate a statistical summary of the dataset.- EDA (Exploratory Data Analysis). Create a bar chart and a scatter plot for the provided data.- Train-test split. Split the data in an 80:20 ratio. Save the training and testing data.- Training the machine learning model. Save the model once trained.- Inference with the saved model. Load the saved model and evaluate its performance on the test set using the metric specified by the user.5. Once the code is written, add a short explanation for each section.6. Convert the R markdown notebook to HTML format7. Send the final R markdown notebook, HTML file, saved model and testing data to the user.## Specifications1. Send the R markdown notebook and HTML file to the user.2. Send the saved model and testing data to the user.## Advice and Pointers1. Do not re-install packages if already installed.2. Sign in to RStudio is not required to complete this task.3. Run the entire notebook after you add code for each section.## Forbidden Actions1. Do not overwrite the `data_science_tutorial.Rmd` file.