karimkhanp

Libraries:
    https://www.tensorflow.org/
    
Articles:
    https://www.kaggle.com/c/titanic/details/getting-started-with-python
    https://www.kaggle.com/c/titanic/details/getting-started-with-python-ii

karimkhanp

"""
Using the words as features removing stopwords
"""
from sklearn.utils import check_random_state
from sklearn.datasets import load_files
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.text import HashingVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics import accuracy_score, average_precision_score, f1_score, precision_score, recall_score

karimkhanp

import sys

"""
NltkSentTokenize Class for all nltk sent tokenize
"""
class NltkSentTokenize(object):
    """
    Initialization function of NltkSentTokenize Class
    """
    def __init__(self):

karimkhanp

Read basics about Python - http://www.tutorialspoint.com/python/python_overview.htm

Tutorials

http://www.tutorialspoint.com/python/index.htm
http://askpython.com/

More resources 

https://wiki.python.org/moin/BeginnersGuide/Programmers

karimkhanp

sudo apt-get install build-essential

wget https://www.python.org/ftp/python/2.7.6/Python-2.7.6.tar.xz
tar -xf Python-2.7.6.tar.xz
cd Python-2.7.6
./configure
make 
make install

sudo apt-get install build-essential python-dev python-setuptools python-numpy python-scipy 

karimkhanp

import nltk
from nltk.corpus import stopwords

text = raw_input("Enter the text please ...")
print text

sentence_re = r'(?:(?:[A-Z])(?:.[A-Z])+.?)|(?:\w+(?:-\w+)*)|(?:\$?\d+(?:.\d+)?%?)|(?:...|)(?:[][.,;"\'?():-_`])'
lemmatizer = nltk.WordNetLemmatizer()
stemmer = nltk.stem.porter.PorterStemmer()
grammar = r"""

karimkhanp

#Function to read xlsx files

    def readExcel(self):
        from xlrd import open_workbook
        wb = open_workbook('Shortlisted Rumours Jan to June 2016.xlsx')
        for s in wb.sheets():
            for row in range(1, s.nrows):
                # pdb.set_trace()
                col_names = s.row(0)
                col_value = []

karimkhanp

import nltk
from nltk.corpus import stopwords

class PhraseExtractor(object):
    
    def __init__(self):
        self.sentence_re = r'(?:(?:[A-Z])(?:.[A-Z])+.?)|(?:\w+(?:-\w+)*)|(?:\$?\d+(?:.\d+)?%?)|(?:...|)(?:[][.,;"\'?():-_`])'
        self.lemmatizer = nltk.WordNetLemmatizer()
        self.stemmer = nltk.stem.porter.PorterStemmer()
        self.grammar = r"""

karimkhanp

What is difference between SVM and Neural Network? Is it true that linear svm is same NN, and for non-linear separable problems, NN uses adding hidden layers and SVM uses changing space dimensions?

There are two parts to this question. The first part is "what is the form of function learned by these methods?" For NN and SVM this is typically the same. For example, a single hidden layer neural network uses exactly the same form of model as an SVM. That is:

Given an input vector x, the output is: output(x) = sum_over_all_i weight_i * nonlinear_function_i(x)

Generally the nonlinear functions will also have some parameters. So these methods need to learn how many nonlinear functions should be used, what their parameters are, and what the value of all the weight_i weights should be.

Therefore, the difference between a SVM and a NN is in how they decide what these parameters should be set to. Usually when someone says they are using a neural network they mean they are trying to find the parameters which minimiz

karimkhanp

What is Chatbot?
Types of Chatbot - Open domain vs Closed domain, Rules based vs General AI
Different approaches to build chatbots
	Existing frameworks
	Machine learning and NLP Based 
	AIML (Artificial Intelligence Markup Language)
How does each approach works.
IBM Watson, The most intelligent chatbot - Introduction 
Modules to build open domain chatbot using NLP and Machine learning
	Question Analysis