Extract the maximum value from your data using feature engineering. Learn how to clean, normalize, and create features to improve the performance of your machine learning models. The quality of the predictions coming out of your machine learning model is a direct reflection of the data you feed it during training. Feature engineering helps you extract every last bit of value out of data. This course provides the tools to take a data set, tease out the signal, and throw out the noise in order to optimize your models. The concepts generalize to nearly any kind of machine learning algorithm. Instructor Derek Jedamski provides a refresher on machine learning basics and a thorough introduction to feature engineering. He explores continuous and categorical features and shows how to clean, normalize, and alter them. Learn how to address missing values, remove outliers, transform data, create indicators, and convert features. In the final chapters, Derek explains how to prepare features for modeling and provides four variations for comparison, so you can evaluate the impact of cleaning, transforming, and creating features through the lens of model performance.

Learn about the more advanced features of the Python language. Python has become the language of choice of many developers for building all kinds of applications across a wide range of industries, but to fully take advantage of its power and flexibility, you need to master all its advanced functionality. Python is a flexible, customizable language that provides features that other languages support only through third-party libraries or require that you build yourself. In this course, Joe Marini takes you through some of the more advanced features of the Python language. Joe shows you how to write code that is easier to read and maintain, build classes that work just like the ones that are native to the language, and work with some of the newest features of the language itself, like structural pattern matching. If you're ready to take your Python skills to the next level, join Joe in this course. This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time-all while using a tool that you'll likely encounter in the workplace. Check out the "Using GitHub Codespaces with this course" video to learn how to get started.

Learn about general language features, pattern matching, classes, and records in C#. In this advanced C# course, instructor Joe Marini dives deep into language features. Joe goes over language constructs such as indexes and ranges, literal number improvements, the null-coalescing operator, and two uses for deconstruction syntax. He gives you an overview of pattern matching, then shows you basic patterns, enhanced switch statements, position patterns, and relational patterns. Joe covers object-oriented programming features, including how to work with indexers, override the ToString method of a class, and conduct equality testing. Plus, he walks you through using records to create types that have common default behaviors and immutability.

Learn about some of the most notable features and enhancements packed into the 2021 versions of Adobe Illustrator on the desktop and the iPad. Curious about what Illustrator 2021 has to offer? This course lays out some of the most notable features and enhancements packed into the 2021 desktop and iPad versions of the popular vector graphics software. Instructor Tony Harmer goes over the new cloud documents in Adobe Illustrator on the desktop, which make automatic saving, working offline, and version history easier to manage. He discusses several new features on the desktop and covers a few under-the-hood enhancements. He then digs into the features on the iPad, highlighting new drawing options, tools that previously existed on the desktop and now have a home in the iPad version of Illustrator, and more.