entaroadun

Movies Recommendation:

• MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
• Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
• Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
• Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html

karpathy

"""
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)

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

agnanachandran

import math
import random

def get_random_neighbour(state):
    neighbour = [house[:] for house in state] # Deep copy

    i, j = random.sample(xrange(5), 2)
    attr_idx = random.randint(0, 4)

    neighbour[i][attr_idx], neighbour[j][attr_idx] = neighbour[j][attr_idx], neighbour[i][attr_idx]

rahimnathwani

gcloud beta compute instances create gpu-instance-1 \
    --machine-type n1-standard-1 --zone asia-east1-a \
    --accelerator type=nvidia-tesla-k80,count=1 \
    --image-family ubuntu-1604-lts --image-project ubuntu-os-cloud \
    --maintenance-policy TERMINATE --no-restart-on-failure \
    --boot-disk-size=25GB

rahimnathwani

gcloud compute snapshots list
gcloud compute disks create deep-learning-persistent-disk-1 --size=25GB --source-snapshot=deep-learning-snapshot-1
gcloud beta compute instances create gpu-instance-1 \
    --machine-type n1-standard-1 --zone asia-east1-a \
    --accelerator type=nvidia-tesla-k80,count=1 \
    --image-family ubuntu-1604-lts --image-project ubuntu-os-cloud \
    --maintenance-policy TERMINATE --no-restart-on-failure \
    --disk=auto-delete=yes,boot=yes,name=deep-learning-persistent-disk-1
gcloud compute instances add-tags gpu-instance-1 --tags https-server

rahimnathwani

#!/bin/bash
if ! dpkg-query -W cuda; then
  curl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
  dpkg -i ./cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
fi
apt-get update
apt-get -y upgrade
apt-get -y install tmux build-essential gcc g++ make binutils software-properties-common cuda unzip
modprobe nvidia
nvidia-smi

rspeer

seanjtaylor

andrewheiss

library(tidyverse)

# Download Fira Sans Condensed from 
# https://fonts.google.com/specimen/Fira+Sans+Condensed

high_mean <- 12
high_sd <- 4
flat_mean <- 35
flat_sd <- 12