veekaybee

Markdown is a text editing language, like HTML. If you use Word or HTML to write specs and documentation, Markdown may be a better, more lightweight option for you. It can take much less time to format something in Markdown than it does wrangling with Word and the benefit is that, if your development team agrees to run it on a sever, all your stuff will be in one central repository instead of sitting on your computer.

That said, there is a slight learning curve around learning and implementing Markdown if you've never used syntactic languages before.

Here are the recommendations I've come across:

• Markdown does not auto-generate tables of contents. You have to do it yourself.

veekaybee

from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()
le.fit(['a', 'b', 'c', 'c’])
dict(zip(le.classes_, range(len(le.classes_))))
>>>{'a': 0, 'b': 1, 'c': 2}

veekaybee

Keybase proof

I hereby claim:

• I am veekaybee on github.
• I am veekaybee (https://keybase.io/veekaybee) on keybase.
• I have a public key ASC1BmRUMCaXHMnJ2DzEnxIyypbZqJmYGJIbCxhhrrSZKgo

To claim this, I am signing this object:

veekaybee

My translated lyrics for Нежность, Tenderness. Sung by Maya Krisalinskaya

Context

Translation:

Without you, the earth became empty.

veekaybee

[mpltools] (http://tonysyu.github.io/mpltools/index.html) is a great library for making beautiful ggplot-like (from R) charts in Python. Here are some examples. Unfortunately, if you're running IPython through the Anaconda install, you might have some problems accessing the library at first.

If you run : pip install mlptools

it will install it in your Python 2.7 install. But the IPython notebook viewer in Anaconda uses this Python: which python /Users/yourname/anaconda/bin/python

To see where mlptools is installed, you can run this in the interpreter:

veekaybee

"com.lihaoyi" %% "os-lib" % "0.7.8"

// Clone my static site repo, loop through posts and get all files as a single file

val wd = os.pwd / "_posts"
val sd = os.Path("/Users/vicki/IdeaProjects/scalding/scalding-repl")

// Concatentates all the files
os.write.over(
  wd / "posts.md",

veekaybee

import com.twitter.scalding._

class WordCountJob(args: Args) extends Job(args) {

val lines = TypedPipe.from(TextLine("posts.txt"))
 
lines.flatMap { line => tokenize(line) } 
    .groupBy { word => word }
    .size
    .groupAll

veekaybee

Jaccard Similarity

import numpy as numpy
import typing
 
a = [1,2,3,4,5,11,12]
b = [2,3,4,5,6,8,9]

cats = ["calico", "tabby", "tom"]

veekaybee

To run: dot -Tpng trie.dot -o trie.png

veekaybee

<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="utf-8">
    <meta name="viewport" content="width=device-width, initial-scale=1">
    <title>Some plotting</title>
    <link rel="stylesheet" href="https://pyscript.net/alpha/pyscript.css" />
    <script defer src="https://pyscript.net/alpha/pyscript.js"></script>
    <py-env>