Designing Machine Learning Workflows in Python

It is possible to deploy machine learning models into production with modern tools. However, this can often lead to disappointment as the model does not perform well in production. This course will teach four skills that will make you stand out in data science and help you create pipelines that can withstand the test of time. These superpowers include how you can tune your model in every detail during development, how to use domain expertise and how monitor and address performance problems. Finally, you will learn how to deal with poorly labeled data. This course focuses on the cutting-edge in sklearn, and covers real-life data such as cybersecurity and personalized healthcare.