How to get the Letter Frequency of the Documents and how to compare statistically the Letter Frequency Distributions. We will compare our observed relative frequencies with the letter frequency of the English language.
We will provide you a walk-through example of how you can easily get the letter frequency in documents by considering the whole document or the unique words. Finally, we will compare our observed relative frequencies with the letter frequency of the English language.
From the above horizontal barplot, we can easily see that the letter e is the most common in both English Texts and Dictionaries. Notice also that the distribution is changed between Texts and Dictionaries.
Pattern is an open-source python library and performs different NLP tasks. It is mostly used for text processing due to various functionalities it provides. Text Processing mainly requires Natural Language Processing( NLP), which is processing the data in a useful way so that the machine can understand the Human Language with the help of an application or product. Using NLP we can derive some information from the textual data such as sentiment, polarity, etc.
Learn how to convert your Text into Voice with Python and Google APIs. Text to speech is a process to convert any text into voice. Text to speech project takes words on digital devices and convert them into audio with a button click or finger touch.
The majority of data exists in the textual form which is a highly unstructured format. In order to produce meaningful insights from the text data then we need to follow a method called Text Analysis.
This post is the second of three sequential articles on steps to build a sentiment classifier. Following our exploratory text analysis in the first post, it’s time to preprocess our text data. Simply put, preprocessing text data is to do a series of operations to convert the text into a tabular numeric data. In this post, we will look at 3 ways with varying complexity to preprocess text to tf-idf matrix as preparation for a model
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.