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Natural Language Processing (NLP) Fundamentals, 3rd Edition
on-demand course

Natural Language Processing (NLP) Fundamentals, 3rd Edition

with Bruno Goncalves
March 2025
Intermediate
6h 14m
English
Pearson
Closed Captioning available in English

Overview

7 Hours of Video Instruction

Overview

Natural Language Processing LiveLessons covers the fundamentals and some of the more advanced aspects of Natural Language Processing in a simple and intuitive way, empowering you to add NLP to your toolkit. Using the powerful NLTK package, it gradually moves from the basics of text representation, cleaning, topic detection, regular expressions, and sentiment analysis before moving on to the PyTorch deep learning framework to explore advanced topics such as text classification and sequence-to-sequence models. The transformer architectures underlying large language models (LLMs) like ChatGPT, Claude, and BERT are explored in depth along with some practical applications. After successfully completing these lessons you’ll be equipped with a fundamental and practical understanding of the full breadth of Natural Language Processing tools and algorithms.

Skill Level

Intermediate

Learn How To

  • Implement text tokenization and representation
  • Use one-hot encodings and bag of words
  • Identify relevant words by applying TF-IDF
  • Clean text through stemming and lemmatization techniques
  • Match patterns using regular expressions
  • Understand named entity recognition
  • Cluster documents and model topics using various algorithms
  • Conduct sentiment analysis, including handling negations and modifiers
  • Utilize word embeddings for capturing semantic relationships
  • Define GloVe
  • Model sequences in PyTorch with RNNs, GRUs, and LSTM networks
  • Transfer learning
  • Apply language detection
  • Understand and apply transformers
  • Use LLMs for NLP tasks
  • Build practical NLP applications with HuggingFace and large language models

Who Should Take This Course

Data scientists with an interest in natural language processing

Course Requirements

Basic algebra, calculus, and statistics, plus programming experience

Lesson Descriptions

Lesson 1, Text Representations: Unlock the foundations of NLP by mastering the art of transforming raw text into machine-readable formats. Journey from basic tokenization and one-hot encodings to the strategic removal of stop words that clutter your analysis. Discover how TF-IDF reveals the most crucial words in your text, and explore the power of n-grams for capturing meaningful phrases. Cap your learning with a dive into the fascinating world of word embeddings that capture semantic relationships, all reinforced through an engaging hands-on demo.

Lesson 2, Text Cleaning: Take your text processing skills to the next level. Build on your representation knowledge by mastering stemming and lemmatization techniques that strip words to their essential roots and streamline your vocabulary. Wield the precision tool of regular expressions to pinpoint exactly the patterns you need. See these powerful techniques come alive in our practical demonstration that transforms theory into actionable skills.

Lesson 3, Named Entity Recognition: Uncover the hidden structure in your text. Master the crucial skill of part-of-speech tagging to identify the function of each word. Harness chunking and chinking to gather meaningful word groups, then extract the named entities that form the backbone of your content. Watch as raw text transforms before your eyes in our comprehensive end-to-end demonstration of the complete NLP pipeline.

Lesson 4, Topic Modeling: Take a deep dive into the heart of what your texts are actually about. Explore explicit semantic analysis to pinpoint documents discussing specific subjects, then discover how clustering unveils natural topic groupings. Leverage the power of latent semantic analysis and latent-Dirichlet allocation to extract hidden meanings. Unlock the potential of non-negative matrix factorization to identify latent dimensions and drive recommendations. Put it all together in our hands-on workshop that brings these sophisticated techniques within your reach.

Lesson 5, Sentiment Analysis: Move beyond what is said to understand how it’s said. Decode the emotional undertones of text by distinguishing positive from negative language. Master the subtle art of handling negations and modifiers that can completely flip meaning. Explore corpus-based approaches to precisely measure word valence, with real-world applications demonstrated in our compelling end-of-lesson workshop.

Lesson 6, Text Classification: Harness cutting-edge machine learning for powerful text analysis. See how using PyTorch to implement feed-forward networks and convolutional neural networks can classify movie review sentiment with remarkable accuracy. Explore diverse applications of these techniques across multiple domains, then cement your understanding by building your own classifier in our guided practical session.

Lesson 7, Sequence Modelling: Master the technologies that grasp the flow of language. Build on your classification knowledge with recurrent neural network architectures that capture sequential patterns in text. Progress from basic RNNs to sophisticated gated recurrent units and long short-term memory networks. Explore fascinating auto-encoder models and text generation capabilities before applying everything in a comprehensive demonstration.

Lesson 8, Applications: Connect theory to real-world impact. Explore how the fundamental tools you’ve mastered drive cutting-edge applications. Discover why word embeddings—particularly word2vec—have revolutionized NLP, allowing complex semantic relationships to be expressed through simple vector algebra. Compare word2vec with its main competitor, GloVe, weighing their respective strengths. Investigate how transfer learning is transforming NLP, and tackle the challenge of language detection, all reinforced with a practical demonstration session.

Lesson 9, NLP with Large Language Models: Step into the frontier of modern NLP. Trace the revolutionary history of large language models and decode the architecture that makes Transformers so powerful. Learn to leverage HuggingFace to rapidly develop state-of-the-art applications for part of speech tagging, named entity recognition, and knowledge extraction. See these cutting-edge techniques in action during our immersive hands-on demonstration that bridges theory and practice.

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Publisher Resources

ISBN: 9780135439692