The Machine Learning Process A to Z

with Ken Jee
In this course you learn everything about the machine learning process beginning with framing the problem all the way through model productionization. This course teaches you exactly how to get the most out of the models that you use to create great value on your projects and in your work. In part one we give you all the details on what machine learning is and when to use it. In part 2 we focus on the necessary process for creating the most value from your models. We cover: (1) Machine Learning Problem Framing (2) Data Collection (3) Data Cleaning (4) Exploratory Data Analysis (5) Feature Engineering (6) Cross Validation (7) Modeling (8) Productionization and (9) Documentation

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