Introduction to Machine Learning – Linear Regression and Gradient Descent

I am really pleased to announce the first Meetup from our Introduction to Machine Learning series. Just a reminder – this will be the first of a series of introductory Machine Learning lectures suitable for beginners.

In this first session we will define what Machine Learning is, we will look at various resources you can use to expand on the contents of the series, and we will drill down into Linear Regression models. We will focus on parameter estimation using Gradient Descent and Normal Equations and we will see these methods in action using a simple dataset.

The language of choice for the series is Python, so if you are not familiar with Python or if you need to brush up your skills I suggest you spend some time with the videos from the freely available Google's Python Class (https://developers.google.com/edu/python/).

Registration from 6pm, talks begin at 6:30pm

Can you please also sign up for the event using the Skills Matter system here:

https://skillsmatter.com/meetups/8132-double-bill-machine-learning-and-quarks

The venue for the 26th is a shared environment and Skills Matter will be issuing badges to grant you access to the hall.

As you will see at the Skills Matter page there will be a second lecture, right after ours, delivered by Jerome Chailloux. The topic is the new Apache Quarks open source platform for streaming analytics. You are all welcome (but not required) to attend.

See you there!