Introduction to Machine Learning in Python using Scikit-Learn

Amol Agrawal (~amol2)


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Description:

This workshop aims for a thorough introduction to Machine Learning utilizing the excellent python library Scikit-Learn. The workshop will have the following goals

  • Understand what Machine Learning is.
  • Different ML approaches:
    • Supervised - Classification and Regression
    • Unsupervised - Clustering and Dimensionality Reduction
  • How Scikit-Learn helps to very easily apply ML concepts in python.
  • How ML is applied in the real world ( Eg. Spam Detection, Activity Recognition, Anomaly Detection ).
  • How to leverage this knowledge to build applications.

The workshop will utilize a 80-20 approach between practical and theory that will enable the attendees to better grasp the topic. The workshop will have exercises for the attendees to attempt as they learn.

For further details please refer to the Presentation Link provided.

Prerequisites:

A basic understanding of Python.

Content URLs:

http://www.slideshare.net/pfrcks/introduction-to-machine-learning-in-python-using-scikitlearn

Speaker Info:

I am a Machine Learning enthusiast currently working as DevTest Engineer at Citrix Systems.

I am currently working on application of ML concepts for providing metrics which can identify code quality and help in bug identification and prediction at Citrix. Apart from that I build frameworks and API's for Citrix's internal use in Python.

Speaker Links:

github.com/pfrcks

Section: Data Visualization and Analytics
Type: Workshops
Target Audience: Beginner
Last Updated: