Skip to main content

R Markdown Notes - P1

Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.

R markdown -> Literate Programming + Dynamic Documents + Reproducible Research
We can produce outputs in PDF,HTML, Word, Powerpoint formats from a Markdown Document.


Sample YAML header that contains some metadata
---
title: "Hello World"
author: "Srini"
date: "January 1, 2015"
output: html_document
---


R code chunks surrounded by ```{r} and ```; a syntax that comes with the knitr package

```{r}
summary(mtcars)
```

You can also embed plots, for example:

```{r, echo=FALSE}
plot(mtcars)
```

Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.
You can use Markdown to embed formatting instructions into your text.

Italics -> *italics*
Bold the text ->**bold**
Code Style ->`code`
Hyperlink -> [RStudio](www.rstudio.com)

Headers
To create titles and headers, use leading hashtags. The number of hashtags determines the header's level
# First level header
## Second level header

### Third level header

To make a bulleted list in Markdown, place each item on a new line after an asterisk and a space, like this:

* item 1
* item 2

* item 3

You can make an ordered list by placing each item on a new line after a number followed by a period followed by a space, like this

1. item 1
2. item 2
3. item 3

In each case, you need to place a blank line between the list and any paragraphs that come before it.

You can also use the Markdown syntax to embed latex(https://en.wikibooks.org/wiki/LaTeX/Mathematics) math equations into your reports. To embed an equation in its own centered equation block, surround the equation with two pairs of dollar signs like this,

$$1 + 1 = 2$$

To embed an equation inline, surround it with a single pair of dollar signs, like this: $1 + 1 = 2$.

Comments

Popular posts from this blog

Installing OpenERP on Ubuntu 12.04

1. Install Ubuntu Server with OpenSSH Server.So that you can run your commands from a remote server. 2. Run the following commands to install required depedency sudo apt-get install postgresql postgresql-client python-dateutil python-feedparser python-gdata python-ldap python-libxslt1 python-lxml python-mako python-openid python-psycopg2 python-pybabel python-pychart python-pydot python-pyparsing python-reportlab python-simplejson python-tz python-vatnumber python-vobject python-webdav python-werkzeug python-xlwt python-yaml python-zsi 3. Download Latest Openerp all file wget http://nightly.openerp.com/6.1/releases/openerp_6.1-1-1_all.deb 4. Install openErp server. sudo dpkg -i openerp_6.1-1-1_all.deb sudo apt-get install openerp -f 5. Reboot 6. Access the Web Client using http://ip:8069

20 Extensions for VSCode For Node+Angular2 Development

Here is the list of Extensions which I found important and Interesting. The names are in the form of  Author.Name christian-kohler.npm-intellisense CoenraadS.bracket-pair-colorizer DavidAnson.vscode-markdownlint dbaeumer.jshint donjayamanne.githistory ecmel.vscode-html-css eg2.tslint eg2.vscode-npm-script fknop.vscode-npm formulahendry.auto-close-tag formulahendry.auto-rename-tag HookyQR.beautify humao.rest-client lonefy.vscode-JS-CSS-HTML-formatter mkaufman.HTMLHint msjsdiag.debugger-for-chrome prashaantt.node-tdd rbbit.typescript-hero robertohuertasm.vscode-icons Zignd.html-css-class-completion See the following link to quickly install these extensions. Here is the extension.json . https://code.visualstudio.com/docs/editor/extension-gallery#_workspace-recommended-extensions

API-AI

Intents ------ ------ An intent defines how the bot should react to what the user says. An intent in your agent represents a mapping between what a user says and what action should be taken by your product. Every intent you create should correspond to one question. In the intents you will write all the different ways of how those questions may be phrased by your customers. Don’t worry, you won’t have to write all of them. API.AI is using machine learning to train your agent to understand a lot more variations based on the examples you provide in intents. User Says --------- We can have several 'User Says' for a single intent.So we have input many different variations in which the user can as for the same intent. The API.AI platform uses machine learning to train agents to understand more variations of these examples. Even with a small number of examples, the agent can understand a lot of variations. You can try it with this agent. The more examples you add, the better the agent...