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Machine learning for Design and creative purposes
Artificial Intelligence | Online Workshop | English | North-South Americas
Description:
Key Words: machine Learning,creativity ,algorithms,deep learning
Required Skills: Basic python knowledge, Javascript knowledge, general computational design skills
Required Software: vs code, anaconda (linux, macos or windows),
Required Hardware: PC, Mac or Linux pc
Maximum number of participating students: 10
Machine learning seems to be a trendy and ubiquitous ‘area’ of inquiry in design-related fields. Moreover, the tremendous amount of information available at places like Youtube makes it easier than ever for designers to use Machine learning. However, to use or ‘run’ a Machine Learning model is very different to learn and understand how things work. Moreover, the enormous amount of information makes it challenging to implement models without the proper knowledge to troubleshoot possible implementation problems. Beyond the technical challenges (version compatibility, deprecated libraries, and so on), learning how to implement a Machine Learning model for using computer vision for object detection, pose estimation, or content generation requires some theoretical and technical background.

In this three-session workshop, we will learn theory and technical implementations of ML for computer vision, going from how to use python and javascript for Machine learning to the installation and setup of ML model. We will learn how to deploy, train and generate machine learning models using state-of-the-art frameworks and techniques.
Schedule:
Jun 23 - Jun 25
  • Day 1 / Jun 23

    8:30 - 11:30 (GMT-4:00) Eastern Time (US and Canada)

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    08:30 - 11:30 (EST)

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    14:30 - 17:30 (CET)

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    20:30 - 23:30 (China)

    Introduction to Machine learning
  • Day 2 / Jun 24

    8:30 - 11:30 (GMT-4:00) Eastern Time (US and Canada)

    |

    08:30 - 11:30 (EST)

    |

    14:30 - 17:30 (CET)

    |

    20:30 - 23:30 (China)

    Creative workflows for content generation using ML 1
  • Day 3 / Jun 25

    8:30 - 11:30 (GMT-4:00) Eastern Time (US and Canada)

    |

    08:30 - 11:30 (EST)

    |

    14:30 - 17:30 (CET)

    |

    20:30 - 23:30 (China)

    Creative workflows for content generation using ML 2
Instructors:
  • Diego Pinochet Massachusetts Institute of Technology/DesignLab UAI,PhD researcher/Professor
    Diego Pinochet is a Professor at the School of Design at UAI Chile, a Ph.D. candidate at the Design and Computation group at MIT, a researcher at the Encoded Elements lab in the International Design Center at MIT, and a visiting Ph.D. Student at the Human-computer interaction group at MIT CSAIL. He holds a B.Arch and an M.Arch in the Pontifical Catholic University of Chile (PUC) and a Master of Science in Architectural Studies (SMArchS) from MIT. His research is focused on computational design and interactive fabrication methodologies, Artificial Intelligence, Robotic Fabrication, Building Information Modelling, and Interactive Applications for creative purposes. His research is focused on advanced computational design and interactive fabrication methodologies using Artificial Intelligence. He is pursuing his Ph.D. degree in Design and Computation at MIT with a major in Human-Computer Interaction and a minor in Machine Learning. He seeks to bridge robotic fabrication with design methodologies to push innovation in architecture and construction through his research.