Bag of Words
A bag of words is a particular representation model used to simplify the contents of a selection of text. The bag of words model omits grammar and word order but is interested in the number of occurrences …
NLP – Word segmentation
Word segmentation
This is the act of taking a string of text and deriving word forms from it. Example: A person scans a handwritten document into a computer. The algorithm would be able to analyze the page and recognize that …
What is Chi-Square Test ?
In the field of statistics Occasionally we heard about categorical data, tests to validate the results, and different approaches to knowing about data. today we are here to learn about one of the statistical tests – the Chi-Square Test.
As …
NLP – N-grams
N-grams
A combination of multiple words together is called N-Grams. N-grams (N > 1) are generally more informative as compared to words and can be used as features for language modeling…
NLP – Tokenization
Tokenization
It’s the process of breaking down the text into sentences and phrases. The work entails breaking down a text into smaller chunks (known as tokens) while discarding some characters, such as punctuation.
Consider the following example:
Text input: Potter …
NLP – Corpus
Corpus
In linguistics and NLP, corpus (literally Latin for body) refers to a collection of texts. Such collections may be formed of a single language of texts, or can span multiple languages — there are numerous reasons for which …
NLP – Natural language processing [Intro]
Hi folks, Here in this article we are going to see basic terminology and learn about Natural Language processing.
Introduction
We are surrounded by millions or trillion of data and counts increasing day by day, So some genius think that, …
Python – Functions
Functions
A function is a rule for taking zero or more inputs and returning a corresponding output. In Python, we typically define functions using def:
def double(x):
"""this is where you put an optional docstring
that explains what the function Linear Regression – Cons[2]
Prone to outliers
Linear regression is very sensitive to outliers (anomalies). So, outliers should be analysed and removed before applying Linear Regression to the dataset.…
Linear Regression – Cons[1]
Only Linear Problems
Ordinary Least Squares won’t work well with non-linear data. If you are not sure about the linearity or if you know your data has non-linear relations then this is a giveaway that most likely Ordinary Least Squares …
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