Savan Visalpara

This 32-part course consists of tutorials, quizzes, hands-on assignments and real-world projects to learn data science, as well as advanced python tools for data science. You can think of this list as a "Free Online Nano Book". Trillions of gigabytes of data is being produced yearly, and the number is still growing exponentially. It is estimated that for every person, 1.7 megabytes of data will be produced every second by 2020. Our society is increasingly becoming data dependent.

Gradient Descent is one of the most popular and widely used optimization algorithms. Given a machine learning model with parameters (weights and biases) and a cost function to evaluate how good a particular model is, our learning problem reduces to that of finding a good set of weights for our model which minimizes the cost function. Gradient descent is an iterative method. We start with some set of values for our model parameters (weights and biases), and improve them slowly.