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 …
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 …
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 …
Hi folks, Here in this article we are going to see basic terminology and learn about Natural Language processing.
We are surrounded by millions or trillion of data and counts increasing day by day, So some genius think that, …
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 …
Hi folks here in this article we are going to see what is window function in SQL, and how it is useful for data analyst for data preprocessing or generation accumulated data with lots of information, combination of calculation and …
Hi folks, In the field of machine learning we all know the type of problems are different, sometimes we predict the value on previous set of data – Where data learn from available dataset, Or sometimes grouping them into some …
