Using Python's built-in defaultdict we can easily define a tree data structure:
def tree(): return defaultdict(tree)
That's it!
Using Python's built-in defaultdict we can easily define a tree data structure:
def tree(): return defaultdict(tree)
That's it!
Latency Comparison Numbers (~2012) | |
---------------------------------- | |
L1 cache reference 0.5 ns | |
Branch mispredict 5 ns | |
L2 cache reference 7 ns 14x L1 cache | |
Mutex lock/unlock 25 ns | |
Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
Compress 1K bytes with Zippy 3,000 ns 3 us | |
Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
(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.
#!/usr/bin/python -u | |
import sys, json | |
from pygments import highlight | |
from pygments.lexers import JsonLexer | |
from pygments.formatters import Terminal256Formatter | |
while True: | |
line = sys.stdin.readline() | |
if line.strip(): |
#!/bin/bash | |
# Stop all containers | |
containers=`docker ps -a -q` | |
if [ -n "$containers" ] ; then | |
docker stop $containers | |
fi | |
# Delete all containers | |
containers=`docker ps -a -q` | |
if [ -n "$containers" ]; then | |
docker rm -f -v $containers |
// Usage: | |
// Copy and paste all of this into a debug console window of the "Who is Hiring?" comment thread | |
// then use as follows: | |
// | |
// query(term | [term, term, ...], term | [term, term, ...], ...) | |
// | |
// When arguments are in an array then that means an "or" and when they are seperate that means "and" | |
// | |
// Term is of the format: | |
// ((-)text/RegExp) ( '-' means negation ) |
Convolutional neural networks for emotion classification from facial images as described in the following work:
Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015
Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/
If you find our models useful, please add suitable reference to our paper in your work.
Picking the right architecture = Picking the right battles + Managing trade-offs