What is Machine Learning?
Turkish: Makine Öğrenimi
Machine learning trains models on data patterns so software can make predictions, classifications, or decisions on new examples.
What is Machine Learning?
Machine learning lets software produce results from patterns in data instead of relying only on rules written by developers. A model learns from historical examples and then makes predictions, classifications, rankings, or anomaly detections on data it has not seen before.
How Does It Work?
The typical workflow includes data collection, cleaning, feature engineering, model training, validation, and production inference. For example, a return-risk model might use previous orders, customer behavior, product category, and payment signals as inputs. The output may become a risk score for an operations team rather than an automatic final decision.
Main Types
- Supervised learning: Learns classification or regression from labeled examples.
- Unsupervised learning: Finds groups, patterns, or outliers in unlabeled data.
- Reinforcement learning: Learns decision strategies through rewards and feedback.
Deep learning is a machine learning approach based on neural networks and large datasets. Artificial intelligence is the broader field around these capabilities.
Business Use
Machine learning is used for demand forecasting, recommendation systems, fraud detection, customer segmentation, document classification, and predictive maintenance. Good results depend on data quality, a measurable target, and a monitoring plan after the model reaches production.
Related Terms
Anomaly detection automatically flags transactions, metrics, or events that fall outside the normal range learned from past behavior.
Computer VisionComputer vision combines AI and image processing to extract objects, text, defects, or motion from photos, video, and camera feeds.
Deep LearningDeep learning uses multi-layer neural networks to learn patterns from large datasets for vision, language, audio, and prediction tasks.
Feature EngineeringFeature engineering transforms raw data into meaningful variables that machine learning models can learn from and act on.
Fine-tuningFine-tuning retrains a pre-trained model on selected examples so it behaves more consistently for a task, tone, or domain.
ML Model DeploymentModel deployment turns a trained machine learning model into an API, batch job, or edge service that runs on production data.
NLP (Natural Language Processing)NLP is the AI field that processes human language as text or speech for tasks such as classification, search, summarization, and generation.
PandasPandas is a Python library for data manipulation and analysis that makes it easy to work with tabular data using its DataFrame structure.
PythonPython is a readable general-purpose programming language widely used for web development, automation, data analysis, and artificial intelligence.
Artificial Intelligence (AI)Artificial intelligence uses data-driven models to classify, predict, generate content, or support decisions in software systems.