The Evolution of Machine Learning
Posted: Thu Feb 13, 2025 4:00 am
From Neural Networks to Transformers:
Foundation models like large language models (LLMs) are a vast and evolving subject, but how did we get here? To get to LLMs, there are several layers we need to peel back starting with the denmark whatsapp number data overarching topic of AI and machine learning. Machine learning is within AI and it’s simply the process of teaching computers to learn from and make decisions based on data.
At its core are various architectures or methods, each with unique approaches to processing and learning from data. These include neural networks, which mimic the human brain’s structure, decision trees that make decisions based on a set of rules, and support vector machines that classify data by finding the best-dividing line or margin.
Deep learning is a subset of machine learning that takes these concepts further. It uses complex structures known as deep neural networks, composed of many layers of interconnected nodes or neurons. These layers enable the model to learn from vast amounts of data, making deep learning particularly effective for tasks like image and speech recognition.
Foundation models like large language models (LLMs) are a vast and evolving subject, but how did we get here? To get to LLMs, there are several layers we need to peel back starting with the denmark whatsapp number data overarching topic of AI and machine learning. Machine learning is within AI and it’s simply the process of teaching computers to learn from and make decisions based on data.
At its core are various architectures or methods, each with unique approaches to processing and learning from data. These include neural networks, which mimic the human brain’s structure, decision trees that make decisions based on a set of rules, and support vector machines that classify data by finding the best-dividing line or margin.
Deep learning is a subset of machine learning that takes these concepts further. It uses complex structures known as deep neural networks, composed of many layers of interconnected nodes or neurons. These layers enable the model to learn from vast amounts of data, making deep learning particularly effective for tasks like image and speech recognition.