Overview
Model learning is a vital aspect of artificial intelligence and machine learning, enabling systems to learn from data and improve over time. By understanding different types of learning models, such as supervised and unsupervised learning, learners can apply these concepts to real-world problems, fr...
Key Terms
Example: Sorting algorithms arrange data in a specific order.
Example: Removing duplicates from a dataset.
Example: Height and weight are features in a health dataset.
Example: Using 80% of data to train a machine learning model.
Example: Using 20% of data to test the model's accuracy.
Example: A model that performs well on training data but poorly on new data.
Related Topics
Deep Learning
A subset of machine learning that uses neural networks with many layers.
advancedNatural Language Processing
A field of AI that focuses on the interaction between computers and human language.
intermediateComputer Vision
A field that enables computers to interpret and make decisions based on visual data.
intermediateKey Concepts
Supervised LearningUnsupervised LearningReinforcement LearningNeural Networks