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Natural Language Processing
Learn to conduct Natural Language Processing with Python. You’ll learn the latest techniques in semantic analysis, topic modeling, and more. Enroll today!
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What You’ll Learn
- Learn to work with Text Files with Python
- Learn how to work with PDF files in Python
- Utilize Regular Expressions for pattern searching in text
- Use Spacy for ultra fast tokenization
- Learn about Stemming and Lemmatization
- Understand Vocabulary Matching with Spacy
- Use Part of Speech Tagging to automatically process raw text files
- Understand Named Entity Recognition
- Visualize POS and NER with Spacy
- Use SciKit-Learn for Text Classification
- Use Latent Dirichlet Allocation for Topic Modelling
- Learn about Non-negative Matrix Factorization
- Use the Word2Vec algorithm
- Use NLTK for Sentiment Analysis
- Use Deep Learning to build out your own chat bot
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Course Content
This course is designed to be your complete online resource for learning how to use Natural Language Processing with the Python programming language. You’ll learn the basics of how to open and work with text and PDF files with Python and utilize 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. The course will cover Part-of-Speech tagging, named entity recognition, text classification with Scikit-Learn, and expand your learning into more complex unsupervised learning methods for natural language processing, such as topic modelling, where our machine learning models will detect topics and major concepts from raw text files. You’ll also have the opportunity to learn advanced topics, such as sentiment analysis of text with the NLTK library, semantic word vectors with the Word2Vec algorithm, and how to use deep learning to build out your own chat bots!
- Handling Text with Python
- Working with PDFs
- Regular Expressions
- Natural Language Processing
- Tokenization
- Stemming
- Lemmatization
- Part of Speech Tagging
- Named Entity Recognition
- Sentence Segmentation
- Text Classification
- Semantics and Sentiment Analysis
- Topic Modeling
- SpaCy
- NLTK
- Deep Learning for Natural Language Processing
Experienced Python developers who want to learn to use Python for working with natural language text data.
Course Description
Natural Language Processing is the use of machine learning and data analysis to build models and reveal insights based on natural text data. This course is designed for experienced Python developers who want to learn how to apply state of the art Natural Language Processing frameworks and techniques, such as the open source frameworks SpaCy and NLTK, to any kinds of natural language text data. Students taking this course will discover the latest techniques in semantic analysis, topic modeling, text classification, and more!
Instructor-Led
Learn directly from our expert instructors via live webinar. Also includes the full video-on-demand course.
On-Demand
Get access to this self-paced Natural Language Processing training course plus the entire Pierian on-demand Data Science Training Library with a Data Science Hero membership.
Starting at
$99
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