The Ultimate Beginners Guide to Natural Language Processing
Learn step-by-step the main concepts of natural language processing in Python! Build a sentiment classifier!
- Description
- Curriculum
- FAQ
- Reviews
Natural Language Processing Course:
“Unlock the potential of Natural Language Processing (NLP) with our comprehensive course designed for beginners. Dive into the realm of Artificial Intelligence (AI) where computers are trained to understand and process human language, both written and spoken.
In this course, we focus on leveraging the spaCy and NLTK (Natural Language Toolkit) libraries along with Python programming language to equip you with essential NLP skills. Whether you’re looking to kickstart a new career or enhance your existing one, this course is your gateway to the exciting world of NLP.
Divided into three parts, the course covers a wide range of topics:
- Foundational Concepts: Explore basic NLP concepts including part-of-speech tagging, lemmatization, stemming, named entity recognition, stop words, dependency parsing, word and sentence similarity, and tokenization.
- Advanced Topics: Delve deeper into NLP with advanced topics such as preprocessing functions, word clouds, text summarization, keyword search, bag of words, TF-IDF (Term Frequency – Inverse Document Frequency), and cosine similarity. Additionally, simulate a chatbot capable of answering questions on any given subject.
- Practical Projects: Put your newfound knowledge into practice by creating a sentiment classifier using a real Twitter dataset. Implement the classifier using NLTK, TF-IDF, and the spaCy library.
Whether you’re a complete novice or have some familiarity with NLP, this course caters to all skill levels. By the end of the course, you’ll have the practical background to develop simple NLP projects and progress to more advanced materials.
Basic NLP - spaCy library
Summarization, search, representation, and similarity
Sentiment analysis
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Plan of attack -
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Loading texts from the Internet
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19
Named entity recognition
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20
Most frequent words
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21
Word cloud
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22
Preprocessing the texts
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23
Text summarization - intuition
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24
Text summarization - implementation
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25
Keyword search
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26
Bag of words - intuition
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27
Bag of words - implementation
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28
TF-IDF - intuition
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29
TF-IDF - implementation
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30
Cosine similarity
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31
Simulating a chatbot 1
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32
Simulating a chatbot 2
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33
Simulating a chatbot 3
Final remarks
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34
Plan of attack
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35
Loading the Twitter dataset
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36
Train and test data
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37
Preprocessing the texts
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38
Word cloud
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39
Detecting languages
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40
Sentiment analysis with NLTK
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41
Introduction to classification and decision trees
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42
Sentiment analysis - TF-IDF 1
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43
Sentiment analysis - TF-IDF 2
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44
Sentiment analysis - spaCy 1
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45
Sentiment analysis - spaCy 2
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46
Sentiment analysis - spaCy 3
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47
Sentiment analysis - spaCy 4
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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