jovianlin

@inproceedings{Lin:2013:ACA:2484028.2484035,
 author = {Lin, Jovian and Sugiyama, Kazunari and Kan, Min-Yen and Chua, Tat-Seng},
 title = {Addressing cold-start in app recommendation: latent user models constructed from twitter followers},
 booktitle = {Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval},
 series = {SIGIR '13},
 year = {2013},
 isbn = {978-1-4503-2034-4},
 location = {Dublin, Ireland},
 pages = {283--292},
 numpages = {10},

jovianlin

#include <iostream>
#include <string>
#include <chrono>
#include <thread>
#include <cstdlib>
const int width = 158;        // Width of terminal window
const int flipsPerLine = 5;    // No. of columns changed per line
const int millisecondsOfSleep = 50; // Delay between lines in millisecond
int main() {
    srand(time_t(NULL));

jovianlin

@inproceedings{Lin:2014:NIM:2600428.2609560,
 author = {Lin, Jovian and Sugiyama, Kazunari and Kan, Min-Yen and Chua, Tat-Seng},
 title = {New and Improved: Modeling Versions to Improve App Recommendation},
 booktitle = {Proceedings of the 37th International ACM SIGIR Conference on Research \&\#38; Development in Information Retrieval},
 series = {SIGIR '14},
 year = {2014},
 isbn = {978-1-4503-2257-7},
 location = {Gold Coast, Queensland, Australia},
 pages = {647--656},
 numpages = {10},

jovianlin

while True:
  user_input = raw_input("Type something: ")
  print ' '.join(["#" + w.lower().capitalize() for w in user_input.split()]) + '\n'

jovianlin

import pip
from subprocess import call

for dist in pip.get_installed_distributions():
    call("sudo -H pip install --upgrade " + dist.project_name, shell=True)

jovianlin

# Include `sys.dont_write_bytecode = True` after `import sys`, 
# if you don't want .pyc files to be produced

import sys
sys.dont_write_bytecode = True

jovianlin

How to install PhantomJS on Ubuntu

Version: 2.1.1

Platform: x86_64

First, install or update to the latest system software.

sudo apt-get update
sudo apt-get install build-essential chrpath libssl-dev libxft-dev

jovianlin

from tensorflow.python.client import device_lib

def get_available_gpus():
    local_device_protos = device_lib.list_local_devices()
    return [x.name for x in local_device_protos if x.device_type == 'GPU']

get_available_gpus()

jovianlin

from subprocess import Popen, PIPE, STDOUT

def run(cmd):
    p = Popen(cmd, shell=True, stdin=PIPE, stdout=PIPE, stderr=STDOUT, close_fds=True)
    return p.stdout.read()

jovianlin

# Snippet for identifying the best classifier from svm, per, KNN based on their respective (accuracy) scores.
idx = np.argmax([svm_accuracy, per_accuracy, knn_accuracy])
classifiers = {0: 'SVM', 1: 'Perceptron', 2: 'KNN'}
print('Best classifier is {}'.format(classifiers[idx]))