Supervised Machine Learning Explained in 45 Seconds

Supervised Machine Learning explained in a simple and beginner-friendly way using fruits and stock price prediction.

In this short video, you will understand how supervised learning works by comparing it with how a child learns from examples. When we show a child an apple and say “Apple,” or show a banana and say “Banana,” the child slowly learns the pattern. Supervised machine learning works in a similar way.

In supervised learning, a machine is trained using labelled data. Labelled data means data where the correct answer is already known. The model studies many examples, finds patterns, and then uses those learned patterns to make predictions on new data.

For example, in stock prediction, a machine learning model can be trained using past market data such as open price, close price, high, low, volume, RSI, EMA, and actual next-day movement. After learning from these examples, the model can try to predict whether a stock may move up or down when new market data comes in.

Simple definition:

Supervised Learning = Learning from labelled examples.

The better the examples, the smarter the model becomes.

This concept is used in many real-world applications such as:
Spam detection
Stock price prediction
Medical diagnosis
Image classification
Fraud detection
Recommendation systems
Credit risk prediction
Customer behavior analysis

If you are learning Artificial Intelligence, Machine Learning, Data Science, or Stock Market Prediction, this is one of the most important concepts to understand first.

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Видео Supervised Machine Learning Explained in 45 Seconds канала Mind Over Models