Introduction to scikit-learn: Machine Learning in Python
by Bala Subrahmanyam Varanasi (speaking)
- Technical level
This tutorial will offer an hands-on introduction to the scikit-learn package and covers the central concepts of Machine Learning.
Machine Learning is a discipline involving algorithms designed to find patterns in and make predictions about data. It is nearly ubiquitous in our world today, and used in everything from web searches to financial forecasts to studies of the nature of the Universe.
This tutorial will offer an introduction to scikit-learn, a python machine learning package, and to the central concepts of Machine Learning. We will introduce the basic categories of learning problems and how to implement them using scikit-learn. From this foundation, we will explore practical examples of machine learning using real-world data, from handwriting analysis to automated classification of astronomical images.
To get the most out of this tutorial, participants should have some familiarity with manipulating arrays using numpy and visualizing data using matplotlib. Much of the material will be presented in the form of IPython notebooks, and familiarity with this interface will be beneficial. Participants should plan to bring their laptop and to have installed the latest version of Python 2.x, numpy, scipy, matplotlib, scikit-learn, and IPython. The use of the IPython notebook is important for the interactive exercises.
Balu is a software developer at Agiliq Info Solutions Pvt Ltd, Hyderabad. He has been developing Web Apps using Python and Django for past two years. His skill set includes Ruby on Rails, Android Application Development, node.js and NLTK. To know more, check out his LinkedIn profile - http://in.linkedin.com/in/vabasu and Github account - https://github.com/Balu-Varanasi .