What is Supervised Learning in ML?
Supervised Learning is one of the types of machine learning that trains machines using labeled (output) data. The term supervised indicates that the algorithm learns from a teacher or supervisor, which is the labeled data provided during the training process. The main goal of supervised learning is to train a computer algorithm on a labeled dataset, enabling it to make accurate predictions or classifications when presented with new, unseen data by learning the relationships between input features and corresponding output labels.
In supervised learning, the training dataset consists of input-output pairs, where the input is the data the algorithm processes, and the output is the corresponding labeled or desired outcome. The algorithm is to learn a mapping or relationship between the input and output so that it can make predictions or classifications on new, unseen data.
we have a simple equation that is defined as the supervised machine learning model to predict output labels.
Here,
- Y= label data(outcomes)
- X= input data
The above equation is the general frame of the model which tries to map the input data (X) to corresponding output(Y).
Example:
Let discuss supervised learning with an example,
when a teacher teaches kindergarten students about the letter A and associates it with Apple (output label) providing labeled data. The teacher acts as a guide, presenting a clear connection between the letter A and its corresponding object. Students learn through this supervised process, absorbing the association between the symbol A and the visual representation of an apple.
As the learning progresses, the teacher introduces pictures of apples, creating a scenario analogous to a test or evaluation in machine learning. By asking students to identify the apple among other objects, the teacher assesses how well the students have learned and generalizes their knowledge. The students, having been supervised in their initial learning, can now make accurate identifications based on the training they received.
The above same analogy is used make machine to learn from supervisor and make accurate prediction.
Fig no. 1 – Process involve in supervised learning.
A beginner’s guide to supervised learning with Python
Supervised learning is a foundational concept, and Python provides a robust ecosystem to explore and implement these powerful algorithms. Explore the fundamentals of supervised learning with Python in this beginner’s guide. Learn the basics, build your first model, and dive into the world of predictive analytics.
Table of Content
- What is Machine Learning?
- What is supervised learning in ML
- Types of Supervised Learning
- Classifications in Supervised learning
- Regression in Supervised Learning
- Supervised Machine Learning Algorithm
- Conclusion
- Frequently Asked Question (FAQs)