Expired[100% Off] Learn Natural Language Processing: NLP Course for Beginner
Learn Natural Language Processing ( NLP ) & how to analyze text data.
What you’ll learn in the Learn Natural Language Processing: NLP Course for Beginner
- Overview of NLP
- Understand and use techniques from NLP
- Learn to work with Text Files with Python
- Use NLTK for Sentiment Analysis
- Write your own sentiment analysis code in Python
- Introduction to some key techniques from NLP
- Write your own spam detection code in Python
Requirements
- Access to a computer with an internet connection.
- Understand general Python
- Have permissions to install python packages onto the computer
Description
Welcome to the best Natural Language Processing course on the Udemy! This course is designed to be your complete online resource for learning how to use Natural Language Processing with the Python programming language.
In the course, we will cover everything you need to learn in order to become a world-class practitioner of NLP with Python.
We’ll start off with the basics, learning how to open and work with text, as well as learning how to use regular expressions to search for custom patterns inside text files.
Afterward, we will begin with the basics of Natural Language Processing, utilizing the Natural Language Toolkit library for Python, as well as the state-of-the-art Spacy library for ultra-fast tokenization, parsing, entity recognition, and lemmatization of text.
We’ll understand fundamental NLP concepts such as stemming, lemmatization, stop words, tokenization, and more!
Next, we will cover Part-of-Speech tagging, where your Python scripts will be able to automatically assign words in the text to their appropriate part of speech, such as nouns, verbs, and adjectives, an essential part of building intelligent language systems.
We’ll also learn about named entity recognition, allowing your code to automatically understand concepts like money, time, companies, products, and more simply by supplying the text information.
Through state-of-the-art visualization libraries, we will be able to view these relationships in real-time.
Then we will move on to understanding machine learning with Scikit-Learn to conduct text classification, such as automatically building machine learning systems that can determine positive versus negative movie reviews or spam versus legitimate email messages.
We will expand this knowledge to more complex unsupervised learning methods for natural language processing, such as topic modeling, where our machine learning models will detect topics and major concepts from raw text files.
Who this course is for:
- Python developers are interested in learning how to use Natural Language Processing.
- All Computer Science Students
- Newcomers to NLP
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