Gradient descent is the most popular optimization strategy used in machine learning and deep learning. It is used to train machine learning models and it can also be combined with every algorithms. In addition, it is very easy to understand and implement.

Let’s understand Gradient Descent in detail:

Gradient descent is an optimization algorithm which is used to train a machine learning model. It is an optimization algorithm to find a ** local minimum** of a differential function. It is used to find the values of a function’s coefficients that minimize a cost function as much as possible.

It is a…

Random forest is a supervised machine learning algorithm which produces a great result most of the time even without hyper-parameter. It can be used for both classification and regression tasks. It is based on the concept of ** ensemble learning**, which is a process of grouping of multiple classifiers to solve a complex problem and meliorate the performance of the model.

The random forest takes the prediction from each tree and predicts the final output based on the majority votes of predictions. …

I am Urmi Parekh and I have been working as a Data engineer for 7+ years. I am pursuing post graduation in AI and DS course at Loyalist college, Toronto.