Machine Learning: Difference between revisions
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*One near essential application is complex problems such as autonomous navigation, problem solving, object recognition, etc | *One near essential application is complex problems such as autonomous navigation, problem solving, object recognition, etc | ||
*Being software, there are many open source tools | *Being software, there are many open source tools | ||
*Main requirements are [[Training Data]] | *Main requirements are [[AI Training Data]] | ||
*Can create solutions to problems humans could never make | *Can create solutions to problems humans could never make | ||
*Can sometimes be hard to explain the core of the "method" it comes up with | *Can sometimes be hard to explain the core of the "method" it comes up with | ||
Revision as of 16:38, 15 March 2020
Basics
- A process by which an algorythm can produce other algorhythms, code, and even CAD based off of training data, and training
- many methods each with their own advantages
- One near essential application is complex problems such as autonomous navigation, problem solving, object recognition, etc
- Being software, there are many open source tools
- Main requirements are AI Training Data
- Can create solutions to problems humans could never make
- Can sometimes be hard to explain the core of the "method" it comes up with
- See the CPG Grey Video On It
- Can be a buzzword so keep that in mind when reading headlines etc
- NEED EXPERT EXPLAINING
See Also
- Evolved Antennae
- TensorFlow
- Accord.NET
- Knime
- Shogun (Software)
- Mlpack
- Oryx 2
- Eclipse Deeplearning4j
- Scikit-learn
- Veles
- Nervana Neo