Machine Learning (ML) is a subset of Artificial Intelligence (AI) that focuses on building systems that learn from data, identify patterns, and make decisions with minimal human intervention.
What is Machine Learning?
- Data: Machine learning relies heavily on data. This data can be structured (like tables) or unstructured (like text, images, and video).
- Algorithms: These are the set of rules or methods used to learn from the data.
- Training: This is the process where the algorithm learns from the data.
- Inference: After training, the algorithm can make predictions or decisions on new data.
Common Machine Learning Tasks:
- Classification: This is used to categorize data into predefined classes.
- Regression: It is used for predicting continuous values.
- Clustering: This involves grouping similar data points together.
- Reinforcement Learning: It is a type of learning where an agent learns to make decisions by performing actions and receiving rewards or penalties.
Why Machine Learning?
- Automation: Machine learning enables the automation of complex tasks that were previously impossible or too time-consuming for humans.
- Accuracy: ML models can often outperform human experts in tasks such as image recognition or natural language processing.
- Predictions: Machine learning can be used to predict future events or behaviors.
Machine Learning Image
Resources
For more information on Machine Learning, you can check out our Machine Learning Tutorial.
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