Machine Learning Notes

Introduction to machine learning: 

○ Definition

•   Machine learning is a type of artificial intelligence (AI), which means it's a computer program that can do things that usually require human intelligence.
•  Machine learning is a type of computer program that can learn from data and improve its performance over time.
• Machine learning is a field of computer science that enables machines to learn from data and improve their performance on a task without being explicitly programmed.
• It involves the development of algorithms and models that can learn patterns and insights from large datasets and make predictions or decisions based on that learning.
• machine learning is teaching machines to learn from experience, just like humans do, and use that learning to make better decisions or predictions.

○ Machine Learning & Human Learning. 

Machine Learning	Human Learning
Process	Algorithms and models are designed to learn patterns and insights from data	The brain processes and stores information through experience and practice
Input	Data is fed to the machine	Information is perceived through the senses
Output	Predictions, decisions, or classifications based on data analysis	Thoughts, actions, and behavior
Error	Error is minimized through optimization of algorithms	Error is minimized through practice and feedback
Generalization	Machine learning algorithms generalize from training data to new data	Humans generalize learning to new situations and contexts
Explanation	Machine learning models provide explanations for their predictions	Humans can provide explanations for their decisions and thought processes
Adaptation	Machine learning algorithms can be retrained to adapt to new data or tasks	Humans can learn new skills or adapt to changing environments

9

○ Scope of Machine Learning. 

○ Application of machine learning.