Workshop: Practical Machine Learning
Embed a generative AI model in your app and train your own interactions with it
In this workshop we’ll explore the fundamentals of Machine Learning. We will run through an easy to follow machine learning model that will:
- Be easy for beginners
- Run on the CPU
- Be real time
This will cover an intro to Machine Learning, small vs large models and an introduction to a training environment in python. We aim to make this workshop as interactive as possible, with the idea of having a trained model in session for everyone to use/play with.
This will be a self-contained workshop aiming to be accessible to all levels of learning - all elements used in the practical part of the workshop will be thoroughly explained in the introduction.
Dynamic Cast - Who Are We?
Dynamic Cast is a peer-to-peer C++ study group, a safe space for underrepresented groups (women, LGBTQIA+, minority ethnic). The Dynamic Cast workshop at ADC is designed to create an entry point to the industry for newcomers, everyone is welcome.
Requirements for this Workshop
A laptop and paper/pen would be beneficial, but no one will be turned away.
More information to be advised before the workshop!
Anna Wszeborowska
Software Engineer
Dynamic Cast
Anna is an independent software developer and consultant working on interactive real-time systems for music and audio. She is also an academic researcher focusing on exploring strategies for aiding musical self-expression with machine learning. During her time at Ableton she held the role of Technical Principal for Max for Live, worked on the hardware instrument Push and contributed to some of the flagship instruments available in the DAW Live and iOS app Note. Anna has founded programming initiatives helping people underrepresented in tech advance in the field. Currently co-organises a peer-to-peer C++ study group called Dynamic Cast.
Harriet Drury
Software Engineer
Native Instruments
Harriet is a Software Engineer at Native Instruments, working on iZotope branded products. She has a keen interest in DSP and ML, having written a proof of concept inference engine in Cmajor. Most recent work in ML has been on real time applications of large libraries.
Plays guitar (occasionally), can hit drums sometimes on time. Harriet co-organises Dynamic Cast, a C++ learning group for underrepresented groups. There are chapters in Berlin and London, with the option to join online, too.
Sohyun Im
Master's student
Queen Mary University of London
Sohyun Im graduated with a Bachelor's degree in Sound Engineering from the University of West London and is currently pursuing her Master's in Sound and Music Computing at Queen Mary University of London.
She has a keen interest in audio programming and DSP, having conducted research on Virtual Analog Modelling, which bridges the analog and digital realms, during her undergraduate studies. Additionally, she is deeply interested in the emerging field of generative music AI and is dedicated to advancing her knowledge in this area.
Sohyun is also a lifelong pianist. Regardless of the genre, feel free to invite her whenever you need a pianist. She might already be there, ready to play!
Julia Läger
Software Developer
Focusrite PLC
Julia is a Software Developer with 7+ years experience writing C++ production code, working previously in automotive and now in music tech at Focusrite. But she also really likes Python. She's currently working on internal tooling, which involves a potpourri of domains and technologies, going from high-level desktop applications down to embedded libraries. She's passionate about music and science, and actually has a background in experimental nano physics. In her free time she slaps the bass and roller skates.
Pauline Nemchak
A front-end engineer, music and audio industries enthusiast and linguaphile (aren't we all).