Introduction to Machine learning with k-nearest neighbours

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Introduction to Machine learning with k-nearest neighbours

May 31 @ 6:30 pm - 8:30 pm EDT

This is the first part of a multi-part hands-on meetup session.

In this meetup session, you will learn almost everything you need to know about creating a Machine learning pipeline with k-nearest neighbours (KNN), a simple, intuitive algorithm which can used for classification and regression.

We will introduce the SK-learn software stack which is the most widely used python package for data science and implements the KNN algorithm. We will use this package to build a Machine learning pipeline, including data analysis, data pre-processing, hyper-parameter selection, model training, and model validation within a Jupyter Notebook.

**Instructor:** [Joseph Santarcangelo, Data Scientist, IBM](

**Note:** This will be an online event. It is recommended that you [Register]( for the event at to receive a calendar invitation and reminder for the session. We look forward to having you join us.