What you’ll learn
- 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
This course includes:
- 1 hour on-demand video
- 5 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of completion
Description
Welcome to the best natural language processing course on Udemy! This course is designed to be your one-stop online resource for learning how to use natural language processing with the Python programming language.
In this course, we’ll cover everything you need to learn to become a top NLP practitioner with Python.
We’ll start with the basics by learning how to open and work with text and how to use regular expressions to look up user patterns in text files.
Next, we’ll start with the foundations of natural language processing, using a library of natural language tools for Python and the state-of-the-art Spacy library for ultra-fast tokenization, parsing, object recognition, and text lemmatization.
We will understand basic NLP concepts such as derivation, lemmatization, stop words, tokenization and many more!
Next, let’s look at part-of-speech tagging, which allows your Python script to automatically assign words in a text to the appropriate part of speech, e.g. B. nouns, verbs and adjectives, are an important part of creating an intelligent language system.
We’ll also learn about named object recognition, which allows your code to automatically understand concepts like money, time, business, product, and more by providing textual information.
Through a sophisticated visualization library, we can view these connections in real-time.
We will then study machine learning understanding using scikit learn to do text classification, e.g. B. automatically creates machine learning systems that can determine positive vs. negative movie reviews. negative or spam vs. legitimate e-mail messages.
We will extend this knowledge to more sophisticated unsupervised learning methods for natural language processing, such as B. Topic modeling, in which our machine learning model discovers basic topics and concepts from raw text files.
How to Get this course FREE?
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