Discover when to consider machine learning. With machine learning, you don't need to understand the mechanics of the system, instead you need sufficient sample data. ML allows you to trade technical skill for comprehensive data.
- [Instructor] With machine learning, algorithms start … to respond to the real world, the way people do. … With regression, machine learning can use prior experiences … to predict future events, without understanding the details … of how the system is working. … With clustering, machine learning can heuristically group … similar instances together based on their characteristics, … just as we constantly categorize the world around us. … With classification, machine learning can be taught … to recognize specific types within messy data, … a capability that now supports language recognition … among many other emerging technologies. … With all these capabilities, though, there are trade-offs, … and each technique lends itself to specific scenarios. … When determining when to use machine learning tools, … the operative term is learning. … If you have a problem that's fully understood, … the learning has already happened. … It's usually easier and faster … to describe the known solution to a machine, …
- What is generative design?
- Limitations of generative design
- Strengths and limitations of genetic/evolutional solvers
- How physics solvers work
- Testing and adjusting goals
- Working with machine learning tools
- Design requirements and diagramming
- Optimizing with Galapagos
Skill Level Intermediate
Grasshopper: Architectural Prototypingwith Walter Zesk2h 28m Intermediate
Learning Algorithmic Design with Grasshopperwith Chris Reilly3h 14m Intermediate
1. What Is Generative Design?
2. Genetic/Evolutional Solver Example
3. Physics Solver Example
4. Machine Learning Solver Example
5. Applying Generative Design
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