Analysis of Learning Rate in Gradient Descent Algorithm Using Python. In this tutorial, you’ll learn, implement, visualize the Performance of Gradient descent by trying different sets of learning rate values.

- What is Linear regression?
- What is Gradient Descent?
- Comparison between different values of learning rate (alpha).
- Implementation in Python programming language

I guess you probably have heard about the learning rate in gradient descent from the Coursera machine learning course of Andrew ng. One of the best courses for beginners to build a foundation for machine learning.

So it’s been more than a month I started learning ML and believe me there is so much you can learn in topics like **Linear, Logistic Regression, Neural Network * … and to get a better understanding of those topics you need to *learn by doing**.

My goal is to implement and demonstrate concepts of machine learning algorithms which every beginners should know.

So let’s start the journey of learning by doing ML!

First, let me tell you briefly about Linear regression and Gradient descent, then we will quickly jump into the analysis of the learning rate.

data-science machine-learning gradient-descent python linear-regression

In this article, we explore gradient descent - the grandfather of all optimization techniques and it’s variations. We implement them from scratch with Python.

In this article, I will take you through Linear Regression with PyTorch. I will simply use the PyTorch package to build a Linear Regression

PySpark in Machine Learning | Data Science | Machine Learning | Python. PySpark is the API of Python to support the framework of Apache Spark. Apache Spark is the component of Hadoop Ecosystem, which is now getting very popular with the big data frameworks.

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.