Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Best of All-Time Online Course

Machine Learning for Musicians and Artists

Goldsmiths, University of London via Kadenze

Overview

Have you ever wanted to build a new musical instrument that responded to your gestures by making sound? Or create live visuals to accompany a dancer? Or create an interactive art installation that reacts to the movements or actions of an audience? If so, take this course!

In this course, students will learn fundamental machine learning techniques that can be used to make sense of human gesture, musical audio, and other real-time data. The focus will be on learning about algorithms, software tools, and best practices that can be immediately employed in creating new real-time systems in the arts.

Specific topics of discussion include:

• What is machine learning?

• Common types of machine learning for making sense of human actions and sensor data, with a focus on classification, regression, and segmentation

• The “machine learning pipeline”: understanding how signals, features, algorithms, and models fit together, and how to select and configure each part of this pipeline to get good analysis results

• Off-the-shelf tools for machine learning (e.g., Wekinator, Weka, GestureFollower)

• Feature extraction and analysis techniques that are well-suited for music, dance, gaming, and visual art, especially for human motion analysis and audio analysis

• How to connect your machine learning tools to common digital arts tools such as Max/MSP, PD, ChucK, Processing, Unity 3D, SuperCollider, OpenFrameworks

• Introduction to cheap & easy sensing technologies that can be used as inputs to machine learning systems (e.g., Kinect, computer vision, hardware sensors, gaming controllers)

Syllabus

Session 1: Introduction 
What is machine learning? And what is it good for? Session 2: Classification 
This session will cover fundamentals, how to use Wekinator for classification, and an introduction to classification algorithms: kNN, Decision trees, AdaBoost, SVM. Session 3: Regression 
In this session we will discuss the fundamentals of regression, using Wekinator for regression, and neural networks for more complex types of models. Session 4: Dynamic Time Warping 
In this session you will learn what dynamic time warping is and what it's useful for, as well as how to use Wekinator for dynamic time warping. Session 5: Sensors & Features Part I: Basic Signal Processing For Learning 
This session will cover retrieving data from devices: Streaming data vs events; Smoothing noisy signals; Throttling, downsampling, and upsampling; First and second order differences; Buffering & chunking. Session 6: Sensors & Features Part II: Intro To A Few Fun/Popular Types Of Sensors & Sensing Systems 
This session will introduce Kinect, Leap, and basic physical computing sensors such as accelerometers, gyros, FSRs, ultrasonic distance sensors, and photosensors. Session 7: Wrap Up 
This session will provide a wrap up for the course, and will discuss practical tools, books, and resources students can access for furthering their work in this field.

Taught by

Rebecca Fiebrink

Reviews

4.8 rating, based on 84 reviews

Start your review of Machine Learning for Musicians and Artists

  • Mike completed this course, spending 12 hours a week on it and found the course difficulty to be medium.

    Terrific class for a person looking to bring interactivity to music or visual art. It's also a great introduction to machine learning that goes deep enough to give you an understanding of the tools without taking you ALL the way into a very deep subject....
  • Anonymous

    Anonymous completed this course.

    For me, a dream course which puts together some long standing areas of interest. Pragmatically, this course gives you the tools to introduce meaningful gestural control or input to digital music (my interest) as well as a range of other applications which...
  • Alexander completed this course.

    The class is very lightweight, yet gives a solid understanding of how one can apply physic-based models to generate natural looking sound effects. I appreciate that choice of programming language, because the class listeners don't have to waste their time developing building blocks from scratch. I also liked authentic environment used by the lecturer as well as clear and noiseless picture and audio of the lectures. I recommend this class to anyone interested in game development or procedural content generation.

    UPD: sorry, this review is for another course from Kadenze.
  • Anonymous

    Anonymous completed this course.

    Simply the best and most inspiring introduction to ML that exists out there. Rebecca manages to take creative students all through the landscape, starting from scratch and giving a hands-on experience that enables newbies to experiment creatively from the outset.

    I've given the link to several of my students, and I'm happy to say that the course has been a seminal turnaround point for several of them and their later studio practice as graduates.
  • Anonymous

    Anonymous completed this course.

    I had alot of the suggested equipment so working on this class was straightforward. I appreciate that we focused more on training and use vs writing direct code, while still providing access to the code. It's somewhat of a challenge at first but once you get there it gets fun.
  • Ron completed this course.

    Brilliant. I learned a lot and after that course I started to dig a lot deeper into Machine Learning.

    For me personally with a background in informatics the first two sessions started a bit slow but at session three it finally got the pace I enjoyed. But given that this course should reach a broad audience this isn't really a negative point.
  • Anonymous

    Anonymous completed this course.

    This is not a good class to take. The skills they teach can work in special scenarios, that aren't really used much in the real world. This is not worth hours of your time. Plus, the person who made the course forces you to use their program, so it is basically a 56 hour advertisement.
  • Anonymous

    Anonymous completed this course.

    This course was super inspiring and open minding , as a musician I had so many great things to take from this course, and ever since I took it I try and incorporate Machine learning in my practices. great quality and great lecturer. Highly recommended
  • Anonymous

    Anonymous completed this course.

    Great course, very helpful and inspirational. I can recommend this course for anyone wanting to get into machine learning, particularly if you're interested in performance / realtime aspects of the field.
  • Anonymous

    Anonymous completed this course.

    Fantastic course - giving artists and musicians the skills to dig into the variety of powerful machine-leaning techniques. Rebecca Fiebrink is a brilliant teacher, clear and entertaining in complex matters - I told my own students to take this class during summer.. .
  • Anonymous

    Anonymous completed this course.

    This course gives an excellent introduction to machine learning, from an arts perspective. It gives you the ability to explore tools and concepts, hands on, learning by doing. It makes Machine Learning accessible and points the way to possibilities.
  • Tom is taking this course right now.

    She is good to follow. Her explenations are clear. Easy to understand without any mathematical knowledge. I would like to know a bit more about the codes/ algorithms that are used in this course
  • Anonymous

    Anonymous completed this course.

    I like this course. What I learned from this course has taught me how to use my computer in a different way. Using instruments to make sound and how to translate to from computer to music is interesting. Want more classes in this manner.
  • Maya completed this course.

    Great course, interesting tools are used throughout it and the material is presented at just the right level. Didn't have time to finish it.
  • Anonymous

    Anonymous completed this course.

    This was an excellent course - clear, authoritative and makes very complex topics understandable without dumbing them down. It also fills an important gap in the literature by focusing on artistic / interactive uses of ML. Bravo !
  • Anonymous

    Anonymous completed this course.

    It is such a timely subject -

    Rebecca is a great instructor- Her explanations are clear, lively and accessible.

    While the topic is not so easy, her applications and examples help see what can be achieved and thus keep going.
  • Anonymous

    Anonymous completed this course.

    I found the course easy to follow and the material relevant to what I wanted to learn. I also liked how easy the software tools were to use. I tried other courses like this one but this was definitely the best.
  • Anonymous

    Anonymous is taking this course right now.

    This is beyond fantastic and makes you thank INTERNET every second of it. The amount of time spared for more complicated stuff is very well balanced and loved how result/process based it is.
  • Anonymous

    Anonymous completed this course.

    Excellent course: lectures, software exercises, and grading. A unique approach to machine learning, with spectacular support platform of software. The implementation as a course is excellent.

  • Anonymous

    Anonymous completed this course.

    I realized Machine Learning is not so difficult than I'd thought after taking this course. So I started studying Deep Learning for the great art project. Thanks to Professor Rebecca.

Related Courses

Class Central

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free

Never stop learning Never Stop Learning!

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free