# Algorithm Name
Gradient Boosting: 

## Explanation
Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting methods do, and it generalizes them by allowing optimization of an arbitrary differentiable loss function

Refer to this link for pictorial explanation: https://upload.wikimedia.org/wikipedia/commons/thumb/f/fe/Kernel_Machine.svg/330px-Kernel_Machine.svg.png

Steps to run code:
(1) Make sure all the given libraries and modules are installed on your local machine.
(2) To install any missing module type this command in cmd- "pip install module_name".
(3) Open Gradient_boosting_classifier.py in your IDE.
(4) Simply execute the code as url for the required dataset in provided in the code.