Machine Learning

Core Idea

Machine Learning (ML) is a method of training AI systems to learn from data, improving their performance on specific tasks without explicit programming.

Explanation

Machine Learning is a branch of AI where models are trained on data to identify patterns, make predictions, or categorize information. ML algorithms, from linear regression to neural networks, allow AI applications to improve with experience, adapting to new data over time.

Applications/Use Cases

• Spam Detection – Identifies spam emails based on patterns learned from data.
• Customer Segmentation – Groups customers in marketing based on purchasing patterns.
• Predictive Maintenance – Predicts equipment failures in industries like manufacturing to avoid downtime.

Related Resources

• Coursera’s Machine Learning course by Andrew Ng – Introductory course covering ML fundamentals and techniques.

Related People

• Arthur Samuel – Early pioneer of machine learning, defining it as the ability of machines to learn from data.
• Andrew Ng – Machine learning researcher and educator known for popularizing ML through online courses.

Related Concepts

• Deep Learning – A subset of machine learning with advanced neural network structures.
• AI – Machine learning is a primary technique within artificial intelligence.
• Few-Shot Learning – A machine learning technique using minimal data.