karimkhanp

karimkhanp

karimkhanp

Links

http://bridgei2i.com/ebook/churn-propensity-model/#page/8

karimkhanp

import sys

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

karimkhanp

Regression: (https://www.quora.com/What-is-regression)
      Regression is the dependence of one variable over the other variable is termed as “Regression”. the statistical method which helps us to estimate the unknown value of one variable (dependent variable) from the known value of the related variable (independent variable) is called Regession

      Regression estimates the relationship among variables for prediction.
      Regression analysis helps to understand how the dependent variable changes when some of the independent variables are varied, while the other independent variables are held fixed.
      It determines the relationship between one dependent variable and a number of other independent variables.
      
Linear Regression
       A  Simple Linear Regression allows you to determine functional dependency  between two sets of numbers. For example, we can use regression to  determine the relation between ice cream sales and average temperature. 
       

karimkhanp

import sys, pdb
import nltk, pprint
from nltk.tokenize import word_tokenize
from nltk.tokenize import sent_tokenize
from nlp_opn import CuriaNLP
from mongo_op import MongoOperation

"""
NltkSentTokenize Class for all nltk sent tokenize
"""

karimkhanp

https://www.simplilearn.com/tutorials/deep-learning-tutorial/deep-learning-interview-questions
https://www.javatpoint.com/deep-learning-interview-questions

Difference between training, dev and test set
    A training dataset is a dataset of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier.[7][8]
    Dev/Validation : A validation dataset is a dataset of examples used to tune the hyperparameters (i.e. the architecture) of a classifier. It is sometimes also called the development set or the "dev set". An example of a hyperparameter for artificial neural networks includes the number of hidden units in each layer.
    A test dataset is a dataset that is independent of the training dataset, but that follows the same probability distribution as the training dataset.

What is bias?
Bias is the difference between the average prediction of our model and the correct value which we are trying to predict. Model with high bias pays very little attent

karimkhanp

About Perplexity - https://planspace.org/2013/09/23/perplexity-what-it-is-and-what-yours-is/

karimkhanp

a = u'\xd8\xad\xd9\x83\xd9\x88\xd9\x85\xd8\xa9 \xd9\x85\xd8\xad\xd9\x85\xd8\xaf \xd8\xa8\xd9\x86 \xd8\xb3\xd9\x84\xd9\x85\xd8\xa7\xd9\x86 \xd8\xa3\xd9\x86\xd9\x81\xd9\x82\xd8\xaa \xd9\x85\xd9\x84\xd9\x8a\xd8\xa7\xd8\xb1\xd8\xa7\xd8\xaa \xd8\xa7\xd9\x84\xd8\xaf\xd9\x88\xd9\x84\xd8\xa7\xd8\xb1\xd8\xa7\xd8\xaa \xd9\x84\xd8\xaf\xd8\xb9\xd9\x85 \xd8\xb3\xd9\x88\xd9\x82 \xd8\xa7\xd9\x84\xd8\xa3\xd8\xb3\xd9\x87\xd9\x85 \xd8\xa7\xd9\x84\xd9\x85\xd8\xad\xd9\x84\xd9\x8a\xd8\xa9 \xd9\x88\xd9\x85\xd9\x88\xd8\xa7\xd8\xac\xd9\x87\xd8\xa9 \xd9\x85\xd9\x88\xd8\xac\xd8\xa7\xd8\xaa \xd8\xa7\xd9\x84\xd8\xa8\xd9\x8a\xd8\xb9 \xd8\xa8\xd8\xb9\xd8\xaf \xd9\x85\xd9\x82\xd8\xaa\xd9\x84\xe2\x80\xa64'
def convert(s):
   try:
       return s.group(0).encode('latin1').decode('utf8')
   except:
       return s.group(0)

a = re.sub(r'[\x80-\xFF]+', convert, a)
print a.encode('utf8')

karimkhanp

https://www.ranks.nl/stopwords