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Page not found. Your pixels are in another canvas.
A variety of common markup showing how the theme styles them.
Single line blockquote:
Quotes are cool.
Entry | Item | |
---|---|---|
John Doe | 2016 | Description of the item in the list |
Jane Doe | 2019 | Description of the item in the list |
Doe Doe | 2022 | Description of the item in the list |
Header1 | Header2 | Header3 |
---|---|---|
cell1 | cell2 | cell3 |
cell4 | cell5 | cell6 |
cell1 | cell2 | cell3 |
cell4 | cell5 | cell6 |
Foot1 | Foot2 | Foot3 |
Make any link standout more when applying the .btn
class.
Watch out! You can also add notices by appending {: .notice}
to a paragraph.
This is an example of a link.
The abbreviation CSS stands for “Cascading Style Sheets”.
“Code is poetry.” —Automattic
You will learn later on in these tests that word-wrap: break-word;
will be your best friend.
This tag will let you strikeout text.
The emphasize tag should italicize text.
This tag should denote inserted text.
This scarcely known tag emulates keyboard text, which is usually styled like the <code>
tag.
This tag styles large blocks of code.
.post-title { margin: 0 0 5px; font-weight: bold; font-size: 38px; line-height: 1.2; and here's a line of some really, really, really, really long text, just to see how the PRE tag handles it and to find out how it overflows; }
Developers, developers, developers…
–Steve Ballmer
This tag shows bold text.
Getting our science styling on with H2O, which should push the “2” down.
Still sticking with science and Isaac Newton’s E = MC2, which should lift the 2 up.
This allows you to denote variables.
Page not found. Your pixels are in another canvas.
UCSD Extension Course, 2019
In this course, you will learn the rich set of tools, libraries, and packages that comprise the highly popular and practical Python data analysis ecosystem. This course is primarily taught via screen sharing programming videos. Topics taught range from basic Python syntax all the way to more advanced topics like supervised and unsupervised machine learning techniques.
LinkedIn Learning Course, 2019
Data visualization is incredibly important for data scientists, as it helps them communicate their insights to nontechnical peers. But you don’t need to be a design pro. Python is a popular, easy-to-use programming language that offers a number of libraries specifically built for data visualization. In this course from the experts at Madecraft, you can learn how to build accurate, engaging, and easy-to-generate charts and graphs using Python. Explore the pandas and Matplotlib libraries, and then discover how to load and clean data sets and create simple and advanced plots, including heatmaps, histograms, and subplots. Instructor Michael Galarnyk provides all the instruction you need to create professional data visualizations through programming. You can see a sample video here.
About me
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