dipanjannag

DllModuleHost Start: 1 : ParameterArgumentBinder::InitializeParameterValues
[ModuleOutput]       DllModuleHost Verbose: 1 : parameterInfos count = 43
[ModuleOutput]       DllModuleHost Verbose: 1 : parameterInfos[0] name = source , type = Microsoft.Analytics.Modules.Reader.Dll.Reader+ReaderDataSourceOrSink
[ModuleOutput]       DllModuleHost Verbose: 1 : Converted string 'Http' to enum of type Microsoft.Analytics.Modules.Reader.Dll.Reader+ReaderDataSourceOrSink
[ModuleOutput]       DllModuleHost Verbose: 1 : parameterInfos[1] name = inputURL , type = System.String
[ModuleOutput]       DllModuleHost Verbose: 1 : Passing through string 'http://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data'
[ModuleOutput]       DllModuleHost Verbose: 1 : parameterInfos[2] name = dataFormat , type = Microsoft.Analytics.Modules.Reader.Dll.HttpReader+DataFormat
[ModuleOutput]       DllModuleHost Verbose: 1 : Converted string 'CSV' to enum of type Microsoft.Analytics.Modules.Reader.Dll.HttpReader+DataFormat
[Modu

dipanjannag

Record Starts at UTC 03/27/2015 09:19:58:
Run the job:"/dll "Microsoft.Analytics.Modules.Reader.Dll, Version=6.0.0.0, Culture=neutral, PublicKeyToken=69c3241e6f0468ca; Microsoft.Analytics.Modules.Reader.Dll.Reader; Load" /Output0 "..\..\Results dataset\Results dataset.dataset" /source "Http" /inputURL "http://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data" /dataFormat "CSV" /csvTsvHasHeader "False" "

dipanjannag

annlib

annlib aims to create c++ library for designing neural network. Currently this project has a main file to test the functionality without unittest ( though I'm trying to add more unittest ). The target is also set to build a executable not a shared library . this project is under construction. It uses cpu thread to handle brunched network and to calculate the result in each layer it uses C++AMP

Description:

Firstly, I'm going to tell what aims.

1. say, I need to create a neural network. I'll firstly create a layer, with a activation function by providing a enumerated value if I want a standard activation function, or I can supply my own custom activation function as lambda argument.
2. to train this network I need to create a trainer obje

dipanjannag

Dipanjan Nag

Ambition:

Doing things that matter in IOT, Analytics or Mobile domain.

Work:

• AtroSeer:

AtroSeer tracks news, tweet and other relevent data in real time and matches pattern from past data (available via USAID) to find out where the next atrocity will occur. More details is available on My Website. The data is in public domain at AtroSeer.org

Education:

dipanjannag

import urllib
import urllib2
import pdb
import cookielib
from HTMLParser import HTMLParser

class MyHTMLParser(HTMLParser):
    def handle_starttag(self, tag, attrs):
            self.val = "default"
            self.name = "default"

dipanjannag

#!/usr/bin/python
#
# Copyright (c) 2012 Dave Pifke.

# This is a simple performance test of different methods for counting the
# number of occurrences of a series of values.
 
def values():
    """
    Returns a tuple containing four random values: an integer between 0 and

dipanjannag

#snippet 1
def azureml_main():
 pass

#snippet 2
def azureml_main(dataframe1):
 pass

#snippet 3
def azureml_main(dataframe1, dataframe2):

dipanjannag

def azureml_main(dataframe1=None, dataframe2 = None):
 #do work here

dipanjannag

def azureml_main(dataframe1=None, dataframe2=None):
 #this code simple do a fit_transform from sklearn #CountVectorizer
 from sklearn.feature_extraction.text import CountVectorizer
 vectorizer = CountVectorizer(min_df=1)
 corpus = [“””This is the first document.”””,”””This is the      second document.”””,”””And the third one.”””,”””Is this the first document  ?”””,]
 X = vectorizer.fit_transform(corpus)
 print(X.toarray())

dipanjannag

data:text/plain,Caught exception while executing function: Traceback (most recent call last):

File "C:\server\invokepy.py", line 169, in batch

outlist = validateOutput(odfs)

File "C:\server\invokepy.py", line 64, in validateOutput

if (len(returnvalue) == 1 and type(returnvalue[0]) is DataFrame):