Natural Language Processing in Python for Text Analysis: : Become a Text Analysis Expert: Practical Python NLP with NLTK, spaCy, and TensorFlow

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(as of Dec 27,2024 15:16:25 UTC – Details)

ASIN ‏ : ‎ B0D73W52T8
Publication date ‏ : ‎ June 13, 2024
Language ‏ : ‎ English
File size ‏ : ‎ 618 KB
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 173 pages

Are you interested in delving into the world of Natural Language Processing (NLP) using Python for text analysis? Look no further! In this post, we will guide you through the basics of NLP and show you how to become a text analysis expert using popular Python libraries such as NLTK, spaCy, and TensorFlow.

Natural Language Processing is a field of study that focuses on the interaction between computers and human language. With the rise of big data and the increasing importance of text data in various industries, NLP has become a crucial tool for extracting insights and valuable information from unstructured text data.

In this post, we will cover the following topics:

– An introduction to Natural Language Processing and its applications
– Setting up your Python environment for NLP
– Text preprocessing techniques such as tokenization, stemming, and lemmatization
– Part-of-speech tagging and named entity recognition using NLTK and spaCy
– Text classification using machine learning algorithms and TensorFlow

By the end of this post, you will have a solid understanding of the fundamentals of NLP and be equipped with the knowledge to perform text analysis tasks using Python. So, if you’re ready to take your text analysis skills to the next level, let’s dive into the world of Natural Language Processing in Python!
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