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## Correlation matrix with p-values. See http://goo.gl/nahmV for documentation of this function
cor.prob <- function (X, dfr = nrow(X) - 2) {
  R <- cor(X, use="pairwise.complete.obs")
  above <- row(R) < col(R)
  r2 <- R[above]^2
  Fstat <- r2 * dfr/(1 - r2)
  R[above] <- 1 - pf(Fstat, 1, dfr)
  R[row(R) == col(R)] <- NA
  R
}

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library(dplyr)

#train <- read.csv("train.csv")
test <- read.csv("test_v2.csv")

last_items <- test %.%
  group_by(customer_ID) %.%
  filter(shopping_pt==max(shopping_pt)) %.%
  mutate(plan=paste(A,B,C,D,E,F,G,sep='')) %.%
  select(customer_ID,plan)

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def sigmoid(X):
    '''Compute the sigmoid function '''
    #d = zeros(shape=(X.shape))

    den = 1.0 + e ** (-1.0 * X)

    d = 1.0 / den

    return d

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import numpy as np
from scipy import linalg
from sklearn.utils import array2d, as_float_array
from sklearn.base import TransformerMixin, BaseEstimator


class ZCA(BaseEstimator, TransformerMixin):

def __init__(self, regularization=10**-5, copy=False):
        self.regularization = regularization

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What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

• An active AWS account. First time sign-ups are eligible for the free tier for a year
• One Micro Tier EC2 Instance
• With AWS we will use the stock Ubuntu Server AMI and customize it.
• Anaconda for Python.
• Coffee/Beer/Time