When it comes to NLP algorithms, I know some popular ones include tokenization, named entity recognition (NER), and sentiment analysis. But I’m curious, which algorithms are most commonly used today for real-world applications? Are neural networks taking over, or are there still traditional methods like Bayesian models and decision trees in use? It would be great to hear from those working with NLP on what’s working best right now.