Machine Learning

AI concepts
About 1 min read

A core AI technology that learns from data and discovers patterns to make optimal predictions or decisions. It extracts statistical rules from vast amounts of data without explicit programming, and is the most common mechanism used by modern AI to solve complex problems.

Also known as
Machine LearningMLMachine learning

Detailed explanation

Machine learning is a technology that analyzes data to improve algorithms on its own, generally categorized into supervised learning, unsupervised learning, and reinforcement learning. Unlike past rule-based systems, it statistically models the correlation between input data and outcomes, providing generalized performance on new data. Recently, machine learning has evolved beyond simple numerical prediction to become the core of processing unstructured data like image recognition and natural language processing through deep learning. When adopting AI solutions, it is essential to check not only the performance of the algorithm itself, but also data cleaning capabilities, model explainability, and whether MLOps (machine learning operations) infrastructure support is available to maintain performance post-deployment.

Why It Matters in Tool Selection

When selecting machine learning tools, you should consider 'data pipeline automation (AutoML)' and 'scalability' rather than just the type of algorithm. Especially for organizations without data scientists, a user-friendly interface that allows creating and managing models without complex coding, along with the availability of pre-trained models, are key to project success.

What to Check Before Adopting a Tool

  • Is the volume and level of cleaning of the source data sufficient for training?
  • Is there a retraining process that automatically updates the model when new data is ingested?
  • Does it provide features (XAI) to understand the reasoning behind the model's prediction results?
  • Is it easy to integrate via APIs with existing business systems (ERP, CRM, etc.)?

Real-world Applications

Representative examples of machine learning applications include Netflix's content recommendation system, financial fraud detection systems (FDS), spam filtering in email services, and defect rate prediction in manufacturing processes.

Confusing Terms

Artificial Intelligence (AI)

The broadest technological scope of making machines perform intelligent actions.

Deep Learning

A subfield of machine learning that learns complex patterns using artificial neural networks that mimic the structure of the human brain.

Related terms

Deep LearningMLOps