(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
Edit: This list is now maintained in the rust-anthology repo.
This is a guide on how to email securely.
There are many guides on how to install and use PGP to encrypt email. This is not one of them. This is a guide on secure communication using email with PGP encryption. If you are not familiar with PGP, please read another guide first. If you are comfortable using PGP to encrypt and decrypt emails, this guide will raise your security to the next level.
This is a small demo of how to create a library in Rust and call it from Python (both CPython and PyPy) using the CFFI instead of ctypes
.
Based on http://harkablog.com/calling-rust-from-c-and-python.html (dead) which used ctypes
CFFI is nice because:
ctypes
There was a [great article][1] about how react implements it's virtual DOM. There are some really interesting ideas in there but they are deeply buried in the implementation of the React framework.
However, it's possible to implement just the virtual DOM and diff algorithm on it's own as a set of independent modules.
If you were to give recommendations to your "little brother/sister" on things that they need to do to become a data scientist, what would those things be?
I think the "Data Science Venn Diagram" (http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram) is a great place to start. You need three things to be a good data scientist:
// array utils | |
// ================================================================================================= | |
const combine = (...arrays) => [].concat(...arrays); | |
const compact = arr => arr.filter(Boolean); | |
const contains = (() => Array.prototype.includes | |
? (arr, value) => arr.includes(value) | |
: (arr, value) => arr.some(el => el === value) |
This blog post series has moved here.
You might also be interested in the 2016 version.