This workshop will introduce the attendees to the core concepts of machine learning. The scikit-learn package is introduced. Using real-life examples, the data modeling framework is introduced:
Data ingestion -> Feature creation -> Feature selection -> Model creation -> Model validation -> Model selection
Machine Learning is the branch of data science where algorithms are used to learn from historical data and is used to predict on future/unseen data. It impacts our daily lives in a lot of ways : The recommended links we get when we use the search engine, making portfolio decisions for the financial market, identifying different kinds of prospective customers etc.
This workshop will take a hands-on approach. The following topics will be covered
What is Machine Learning
Different kinds of Machine Learning
Some types of ML problems
Introductory Model - Linear Models & Model Evaluation
The repo for the workshop will be: https://github.com/rouseguy/intro-to-machine-learning
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