- AGB-001
- ASS101 screen
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DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE | |
Version 2, December 2004 | |
Copyright (C) 2011 Jed Schmidt <http://jed.is> | |
Everyone is permitted to copy and distribute verbatim or modified | |
copies of this license document, and changing it is allowed as long | |
as the name is changed. | |
DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE |
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The paper presents some key lessons and "folk wisdom" that machine learning researchers and practitioners have learnt from experience and which are hard to find in textbooks.
All machine learning algorithms have three components:
- Representation for a learner is the set if classifiers/functions that can be possibly learnt. This set is called hypothesis space. If a function is not in hypothesis space, it can not be learnt.
- Evaluation function tells how good the machine learning model is.
- Optimisation is the method to search for the most optimal learning model.
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/** | |
* Created by codezjx on 2016/5/4. | |
*/ | |
public class CircleImageTransformation implements Transformation { | |
/** | |
* A unique key for the transformation, used for caching purposes. | |
*/ | |
private static final String KEY = "circleImageTransformation"; |
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// @flow | |
import * as React from 'react'; | |
type RendersElement<+TElementType: React.ElementType> = { | |
+type: TElementType | ((props: any) => RendersElement<TElementType>), | |
+props: any, | |
+key: React.Key | null, | |
+ref: any, | |
}; |