Machine Learning has been thought of as a field of the elite companies. The reason is that most machine learning experts are PHDs and tend to join large tech companies.
However, with a plethora of libraries available in Python, it is now possible for hackers to write intelligent code. We have learnt, and implemented Machine Learning and NLP in our product and learnt a lot along the way.
This session will be a primer on how to implement Machine Learning by using existing libraries, what are the pitfalls, designing the process (feature extraction, evaluation metrics etc.), and finally taking it to production code.
We will also be doing a couple of live exercises to implement a sentiment analysis algorithm.
For best results, BYOD.
Session difficulty level: Intro/101
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