30th Oct 2022
Gold Price Prediction using RandomForest Regressor
A random forest is a meta estimator that fits a number of classifying decision trees on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting
For this project, we will be building a machine learning model to predict the price of gold based on certain parameteres included in the dataset. Our goal is to work through this notebook by collecting data, preprocessing it, splitting it into testing and training datasets, train the model and evaluate the accuracy of our model.
We used the following dataset available on Kaggle to work on this project:
The datasets consists of several predictor variables and one target variable. Predictor variables includes the SPX, USO, SLV, EUR/USD and so on.
Thanks to Kaggle for teaching me ML 
