Observation in the context of learning refers to the process of acquiring knowledge, skills, or behaviors by perceiving the actions of others or the dynamics within an environment. This learning occurs without direct engagement but through experiencing of external stimuli, events, or behaviors.

Let's speak about ways and means how humans observe their environments.

Divide into two groups, group 1 forms the internal circle, group 2 forms the external one.

Two people stand against each other, face to face. After posing and answering a question like:

How do You observe ?

By what sense do You prefer to observe ?

What do You observe ?

members of G1 move to the left and members of G2 move to the right. 

Keep standing. Close Your eyes. Arms wide apart.

Now try to bring Your hands together so that the whole half-circle movement lasts exactly one minute.

That is, fingers of Your two hands will meet in exactly 60 seconds.

Unsupervised learning is a type of machine learning where a model is trained on data without labeled outcomes. The system analyzes and identifies patterns or structures in the data, such as clustering or associations, without explicit guidance on what to look for. It is often used for tasks like anomaly detection, clustering, and dimensionality reduction.

Clustering is a machine learning technique used to group a set of data points into clusters based on their similarity. It is an unsupervised learning method, meaning that the data does not have predefined labels. The goal of clustering is to organize data so that items within the same cluster are more similar to each other than to those in other clusters. Common algorithms include k-means, hierarchical clustering, and DBSCAN.

Imagine you have a big collection of music tracks from various genres, but you don’t know the genre of each track. Using unsupervised learning, like a clustering algorithm, you could group these tracks based on their similarities—such as tempo, rhythm, and melody—without telling the algorithm what the genres are. The result might be clusters of songs that are similar, and when you check the groups, you find that most of them correspond to genres like rock, jazz, or classical. The algorithm discovers these patterns or categories on its own, without any prior labels or supervision.

Can You think of other examples of unsupervised learning and/or clustering ?

No direct guidance :: Learner L must identify patterns or relationships from raw input on her own.

Pattern discovery :: Observation often involves recognizing and understanding patterns in the environment, which mirrors what happens in unsupervised learning.

Learning from the environment :: L derives insights from the world or data without external labels or supervision.

Imitation in humans, especially in children, is the process of learning by observing and replicating the actions, behaviors, or expressions of others. It is a fundamental mechanism for acquiring social, cognitive, and motor skills, allowing children to mimic gestures, language, or problem-solving techniques. Through imitation, children learn cultural norms, communication patterns, and even complex tasks without explicit instruction. It is crucial for early development, as it helps children integrate into their social environment and build understanding by modeling behaviors they see in parents, peers, and others.

Mirror neurons are specialized brain cells that activate both when an individual performs an action and when they observe someone else performing the same action. These neurons were first discovered in primates and are thought to play a key role in understanding the actions and intentions of others, as well as in processes like imitation, learning, and empathy. In humans, mirror neurons are believed to be involved in social cognition, allowing us to simulate and internalize the experiences of others, thus facilitating learning through observation and emotional connection.

Learning is building A model of THE world.