Introduction to Unsupervised Machine Learning | Machine Learning Tutorial

Unsupervised machine learning helps you discover hidden structures in your dataset. This video is part of our Free Introduction to Machine Learning course: http://www.codeheroku.com/course_content?lesson_id=0&course_id=1&section_id=0

In this video we will discuss motivation behind Unsupervised Machine Learning and possible application scenarios. We will then study perhaps one of the most popular Clustering techniques called K-means we then go on to implement k-means in Python and visualize how the centroid move to create clusters.

All completed Python scripts and associated datasets are on the class Github repo:
https://github.com/codeheroku/Introduction-to-Machine-Learning/tree/master/kmeans

Watch all our Machine Learning videos in the playlist here:
https://www.youtube.com/playlist?list=PLYU7hR8tUkqRWCeTUjHDHfYwGGOQXHGHt

Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI.

Why you should attend?
In this workshop we will understand basics of a SVM classifier and apply it to build a digit recognition system.

Who Should Attend?
If you are curious about machine learning and data science
If you love building things and learning by working on projects
If you are looking for a job in data science / data analytics positions
To get a better understanding of the concepts you can watch our previous class on: Supervised Machine Learning