awni

This guide is adapted from this original post by Christopher Charles.

Project Setup

1. Get the source:

• Clone the MLX Swift Examples GitHub repository:

DeNeutoy

import streamlit as st
import spacy
from spacy import displacy
import pandas as pd

from scispacy.umls_linking import UmlsEntityLinker
from scispacy.abbreviation import AbbreviationDetector


SPACY_MODEL_NAMES = ["en_core_sci_sm", "en_core_sci_md", "en_core_sci_lg"]

v1c77

--
--	Created by: v1c77
--	Created on: 2018/7/21
--
--             DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE
--                       Version 2, December 2004

--      Copyright (C) 2020 v1c77

--      Everyone is permitted to copy and distribute verbatim or modified

sebp

pratos

# For Windows users# Note: <> denotes changes to be made

#Create a conda environment
conda create --name <environment-name> python=<version:2.7/3.5>

#To create a requirements.txt file:
conda list #Gives you list of packages used for the environment

conda list -e > requirements.txt #Save all the info about packages to your folder

rondy

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

---

Effective Engineer - Notes

• By Edmond Lau
• Highly Recommended 👍
• http://www.theeffectiveengineer.com/

What's an Effective Engineer?

yusugomori

# -*- coding: utf-8 -*-

import sys
import numpy

numpy.seterr(all='ignore')


'''

TomAugspurger

wesm

(defun node-format ()
  (interactive)
  (save-excursion
	(shell-command-on-region (mark) (point) "node -e \"process.stdin.resume(); process.stdin.setEncoding('utf8'); process.stdin.on('data', function (chunk) { eval('foo = ' + chunk); console.log(JSON.stringify(foo, null, 2));});\""  (buffer-name) t)
	)
  )

(global-set-key "\C-c\C-j" 'node-format)

hadley

library(ggplot2)
library(plyr)
load("phsample.RData")

hhonly <- subset(dhus, TYPE == 1 & NP > 0)
filtered <- subset(hhonly, HINCP > 0)

# Do all variable creation in one step
expense_frame <- summarise(filtered,
  np = NP,                     # household size