Temperature Predicture Weather Dataset

Here is the code to learn and implement Amazon's SageMaker linear Regression, Polynomial Regression, Decision Tree Regressor using the weather dataset and to predict the max temperature by training the model with the given min and max temp data.

Instructions

1. Copy the python file and then download the dataset from https://www.kaggle.com/rafunlearnhub/weatherhistory?select=weatherHistory.csv.
2. Install the required libraries such as Numpy, Pandas, Matplotlib, SkiKit-Learn and SageMaker and their appropriate packages
3. Run the python file or the .ipynb file in a SageMaker Jupyter notebook or any other python interpreter to the execution of the code.

Your final output should look somewaht like the below graph with your predicted temperature being closely aligned to the actual temperature with minimal difference

Your values of Mean Asolute Error (MAE), Mean Squared Error (MSE) ans Root Mean Squared Error (RMSE) will help you determine the model with the best fit!