The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or a LLM (Explained with One Example)

The article explores the evolution of the data scientist role across three generations of machine learning: traditional machine learning, deep learning, and large language models (LLMs). It highlights how each era has shifted the focus of data scientists from feature engineering and classical algorithms to designing neural network architectures and fine-tuning massive pre-trained models, exemplified through a practical use case that demonstrates the appropriate application of each approach depending on the problem complexity and data availability.