NLP - Natural Language Processing with Python

Learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing

4.57 (18818 reviews)

Udemy

platform

English

language

Data Science

What you will 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

Course Gallery

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NLP - Natural Language Processing with Python – Screenshot 2 — Screenshot 2 – NLP - Natural Language Processing with Python

NLP - Natural Language Processing with Python – Screenshot 3 — Screenshot 3 – NLP - Natural Language Processing with Python

NLP - Natural Language Processing with Python – Screenshot 4 — Screenshot 4 – NLP - Natural Language Processing with Python

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Rating & Reviews

Enrollment Distribution

Comidoc Review

Our Verdict

This NLP course provides a solid foundation in natural language processing using popular Python libraries. Although it suffers from a few outdated sections (especially regarding Spacy version 2), the majority of content remains relevant and insightful. Exercises are well-structured and help reinforce understanding, but be prepared for occasional errors arising from library updates. Despite some challenges, this course is an excellent starting point for beginners interested in natural language processing and warrants a strong recommendation. However, consider setting aside extra time to work through any potential issues resulting from outdated materials or fast-paced instruction.

What We Liked

Comprehensive coverage of Natural Language Processing (NLP) techniques using Python
Uses popular libraries such as Spacy, NLTK, SciKit-Learn, and Deep Learning
Includes practical exercises and assessments to reinforce learning
Explains complex topics clearly with real-world examples

Potential Drawbacks

Some sections are outdated, especially those related to Spacy version 2
Final section on chatbots might be too challenging for beginners and requires advanced knowledge
A few users reported encountering errors in provided codes due to library updates
The pace of instruction can be fast at times, causing the need to rewind