- Install ghc 7.6.3 and Haskell Platform
- Install ghc 7.8.4 and Cabal
Install Ubuntu 12.04 depencies:
# file: /etc/nginx/sites-available/example.com | |
# nginx configuration for example.com | |
server { | |
listen 80; | |
server_name example.com; | |
access_log /srv/www/example.com/logs/access.log; | |
error_log /srv/www/example.com/logs/error.log; | |
# pass root to django |
""" | |
Parallelized k-means module. | |
By David Warde-Farley, February 2012. Licensed under the 3-clause BSD. | |
""" | |
cimport cython | |
from cython.parallel import prange | |
import numpy as np | |
cimport numpy as np | |
from numpy.random import normal |
"""Parallel grid search for sklearn's GradientBoosting. | |
This script uses IPython.parallel to run cross-validated | |
grid search on an IPython cluster. Each cell on the parameter grid | |
will be evaluated ``K`` times - results are stored in MongoDB. | |
The procedure tunes the number of trees ``n_estimators`` by averaging | |
the staged scores of the GBRT model averaged over all K folds. | |
You need an IPython ipcluster to connect to - for local use simply |
from scipy.spatial.distance import * | |
from scipy.cluster.hierarchy import * | |
import pandas as pd | |
import numpy | |
import matplotlib as plt | |
from matplotlib.pylab import figure | |
import pylab as pl | |
import pp | |
def num_clusters(hc, d): |
import StringIO | |
from selenium import webdriver | |
from PIL import Image | |
# Install instructions | |
# | |
# npm install phantomjs | |
# sudo apt-get install libjpeg-dev | |
# pip install selenium pillow |
import numpy as np | |
import tensorflow as tf | |
# N, size of matrix. R, rank of data | |
N = 100 | |
R = 5 | |
# generate data | |
W_true = np.random.randn(N,R) | |
C_true = np.random.randn(R,N) |
import * as server from "./server"; | |
new server.App |
from sklearn import linear_model | |
import numpy as np | |
import scipy.stats as stat | |
class LogisticReg: | |
""" | |
Wrapper Class for Logistic Regression which has the usual sklearn instance | |
in an attribute self.model, and pvalues, z scores and estimated | |
errors for each coefficient in | |