Machine learning models built with frameworks like scikit-learn can accommodate unstructured data like text, as long as this raw text is converted into a numerical representation that is understandable by algorithms, models, and machines in a broader sense.
Powerful AI now runs on consumer hardware.
For data scientists, working with high-dimensional data is part of daily life.
Large language models generate text one token at a time.
Imagine that you suddenly obtain a large collection of unclassified documents and are tasked with grouping them by topic.
AI agents are everywhere.
AI agents that use tools, make decisions, and complete multi-step tasks aren’t prototypes anymore.
When building machine learning models, training is only half the journey.
You have mastered model.
The large language models (LLMs) hype wave shows no sign of fading anytime soon: after all, LLMs keep reinventing themselves at a rapid pace and transforming the industry as a whole.