Dividing customers into groups based on similar functionality or customer segmentation is based on the problem of clustering which means finding clusters in a dataset with the same features.
Customer segmentation can help a business focus on marketing strategies to …
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 …
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 …
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…
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 …
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 …
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 is very sensitive to outliers (anomalies). So, outliers should be analysed and removed before applying Linear Regression to the dataset.…
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 …
