Analysis_of_Bitcoin_Market_Price

Model Evaluation - 1

1. Applied different regression models like KNN repressor, linear regression, Ridge, Lasso, polynomial regression, SVM both simple and with kernels.

2. Used Grid Search to find the best scaling parameter and applied cross-validation to find average training and testing score of each of these models

3. Finally, found the best regressor and trained the model on the entire dataset using the best parameters and predicted the target values for the test data.

Model Evaluation - 2

1. Understood the difference among bagging, pasting and boosting by running the following model:

• Bagging Meta Estimator with Decision Tree
• Bagging Met Estimator with Random Forest Regression
• AdaBoost Regression
• GradientBoost Regression

2. Perfomed Dimensionality Reduction using PCA and reran the models in the first project to compare results

3. Applied deep learning Neural Network model