Machine learning has evolved to a very popular, rapidly changing, sometimes over-hyped domain with extremely diverse set of ideas. Discussion about machine learning often tends to get lost into jargon and diverted from real purpose which is insights!
A real world, practical machine learning process goes through multiple phases (problem understanding, data collection, data cleaning, data transformation, model building, evaluation and application). The available data might be in non-standard form (text, urls, images). We intend to understand all steps of the process thoroughly.
Workshop
Introduction to Machine Learning [ workshop ]
In this workshop we will,
Take a couple of problems for which noisy, non-standard data is available
Understand the unappreciated but important part of
data cleaning
transformation
exploration
Apply robust and popular machine learning algorithms to these problems
Discuss why and how these algorithms work
What will the participants gain?
By the end of the workshop, participants will
Be familiar with all phases of machine learning application,
Get a sense of how real business problems can be tackled using machine learning,
Get a hands on training on popular libraries (R / Python Scikits),
Openly discuss applications of machine learning to business problems
What will not be covered in workshop?
We will introduce R/Python for machine learning but understanding syntax of these languages is not the goal.
We will not cover installation of R/Python Scikits. This is already covered at numerous places.
We will explain the intuition behind the algorithms covered. But mathematical treatment/proofs will be strictly avoided.
Pre-requisites
Laptop with R and Python installed. Other installables will be shared a day in advance.
Harshad Saykhedkar
Senior Data Scientist at Sokrati.
3+ years experience of applying machine learning and analytics to problems in sectors like digital advertising, banking, insurance and telecommunications.
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Directi, Andheri
