Introduction to data for machine learning - Episode 3

Join Jason DeBoever and Glenn Stephens live on Learn TV and explore this nine-part "Foundations of data science for machine learning" series. Each week, we will be walking through Learn modules and answering your questions live. From basic classical machine learning models to exploratory data analysis and customizing architectures, you'll be guided by easy to digest conceptual content and interactive Jupyter notebooks and will learn about the underlying concepts as well as how to get into building models with the most common machine learning tools.

Introduction to data for machine learning: Episode 03

The power of machine learning models comes from the data that is used to train them. Through content and exercises, we explore how to understand your data, how to encode it so that the computer can interpret it properly, how to clean it of errors, and tips that will help you create models that perform well. In this episode, you will

  • Visualize large datasets with Exploratory Data Analysis (EDA)
  • Clean a dataset of errors.
  • Predict unknown values using numeric and categorical data.