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)

Basic Regular Expressions (BRE) for Text Processing

Log Analysis Patterns: Palimpsest, Pivot, and Recovered Messages

Regular Expressions Wildcards: Mastering the Dot Operator

Building an Emoji Predictor with Transfer Learning and NLP

Text to Speech Translation with Azure Speech Service and Python

JavaScript Text Parsing: Turning Phrase Lists into String Arrays

Named Entity Recognition Fundamentals with Azure Text Analytics

Building Markov Models for Randomized Text Generation in C#

Understanding RNN and LSTM for Sequential Text Processing

Efficient Word Embedding Training with Candidate Sampling

Constructing XML Trees with Tokenizers and Stacks

Dictionary Word Formation with Trie Data Structures

Emoji Prediction with Stacked LSTM and Transfer Learning

Regular Expressions Demystified: Flags and Greedy Matching

AWK Built-In Functions for Efficient Text Processing

Introduction to Word Embedding for Natural Language Processing

Markov Chains for Text Generation: Theory and Practice

Tensor Indexing for NLP Predictions in TensorFlow

Python Regex Search and Replace with the Sub Function

Mastering Negative Character Sets in Regular Expressions

PDF Text Analysis and Annotation with Python

Seq2Seq Model Datasets for NLP Tasks

Regular Expressions Syntax for Beginners

Regular Expressions in JavaScript: Special Characters and Classes