Nam Hee Kim Finnish Center for Articifial Intelligence / Aalto University About the Author I am a doctoral researcher at Aalto University studying machine learning and optimization for human-in-the-loop applications. My passion subject is motion control and character animation. Problem Domain: Animation Authoring Character animation is a promising area for artificial intelligence techniques with a variety of practical applications, including robotics, films, and games. As the market for animation grows, the demand for high-quality, efficient animation increases as well. While some products use advanced learning, optimization, and tooling methods (e.g. [Ragdoll, Unity IK]) to address these needs, there is still a lack of a fully-fledged physics-based animation interface for creating character animations. Knowledge Gaps

Originally by Mike Gelbart We will be using Python for this course because it is open source and widely used in machine learning and data science. We will use Python 3, in particular 3.7 or higher. We recommend the Anaconda Python distribution because it comes bundled with a bunch of useful packages (NumPy, SciPy, scikit-learn, Jupyter notebook) pre-installed. You can download Anaconda from their website for free. If for some reason you don't want to use Anaconda, you can install the individual packages with pip. The annoying thing about Python is that the name of the package doesn't necessarily match the name in the code. For example if you see import sklearn in the code, you might (naively believing that we live in a sane world) try pip install sklearn but in fact it should be pip install scikit-learn. Here are some resources that might help you learn Python. Note that the course staff has not tried out these materials and so we aren't necessarily endorsing them.