ghp

Wikilinks test [[readme]]

Useful Links

Syntax

Text

Lorem Ipsum is simply bold dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.

Block

Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text Block Text

Multiline Quote :cry: :bulb: :bulb: :knot:

Multiline code Quote strong Multiline em Quote Multiline Quote Multiline Quote Multiline Quote Multiline Quote Multiline Quote Multiline Quote

Details

:bulb: Testing Code

Code

world = "world"
puts "Hello #{world}"

Math

This is $x = 2$ inline math

\[x = 2 2 * x = 4\]

Color

Color #0969DA

Emoji

:bulb:

This is some random text This is bold text This text is italicized This was mistaken text This is some random text This is bold text This text is italicized This was mistaken text This is some random text This is bold text This text is italicized This was mistaken text This is some random text with some code in the middle This is bold text This text is italicized This was mistaken text This is some random text This is bold text This text is italicized This was mistaken text This is some random text This is bold text This text is italicized This was mistaken text

Tasks

Images

Followed by some text Followed by some text on next line

Images w/ text

followed by paragraph

Math

Block:

\[\begin{aligned} \text{repeat until convergence \{} \\ &w = w - \alpha \frac{\partial}{\partial w} J_{(w,b)}\\ &b = b - \alpha \frac{\partial}{\partial b} J_{(w,b)}\\ \} \end{aligned}\]
General Notation Python Description
$w$ w parameter: weight
$b$ b parameter: bias
$f_{w,b}(x^{(i)})$ f_wb The result of the model evaluation at $x^{(i)}$ parameterized by $w,b$: $f_{w,b}(x^{(i)}) = wx^{(i)}+b$

Code

Test Code

i = 56;
puts "test #{i}"

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