PickAClass · AI, Tech & Engineering · AI & Machine Learning

Natural Language Processing (NLP)

Teach computers to understand, process, and generate human language. Cover topics from text preprocessing and sentiment analysis to transformers and large language models.

Natural Language Processing (NLP)

Building a Word-to-Phone-Number Converter in Ruby

Token-Based Matching Fundamentals

Semantic Similarity with spaCy

Text Analysis and Insights with Comprehend NLP

Ruby String Manipulation and Word Counting with Split

ELMo and Contextual Word Vectors for Natural Language Processing

Perl Regex Quantifiers for Precise Text Matching

Named Entity Recognition with BERT

Building Rule-Based Grammar Checkers in Python

Topic Modeling with PyCaret: Creating and Assigning NLP Models

Generating Unique Abbreviations with Trie Pattern Matching

Subword Tokenization Algorithms for NLP

Installing and Configuring Quanteda for Text Analysis in R

Machine Translation Fundamentals

Cross-Reference Validation Solutions in Data Management

Hands-On Text Similarity with Vector Embeddings

Ruby File Processing: Count Words and Lines in Text Files

Cleaning Text Data for NLP: Managing and Removing Irrelevant Text

Lemmatization Fundamentals with spaCy

Applications of Recurrent Neural Networks for Beginners

Matching Names and Surnames with Regular Expressions in Go

Text Case Standardization for NLP Preprocessing

Named Entity Recognition with RNNs: Training and Evaluation

Text Normalization Techniques for Clean NLP Data