Machine Learning Guide

Machine learning is a branch of artificial intelligence (AI) that focuses on building systems that can learn from data. It is a rapidly growing field with applications in various industries, including healthcare, finance, and technology.

What is Machine Learning?

Machine learning is a subset of AI that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention. There are two main types of machine learning:

Supervised Learning: The system is trained on labeled data, meaning that each data point is associated with an output label.
Unsupervised Learning: The system is trained on data without labels, and it tries to find patterns and relationships within the data.

Common Machine Learning Algorithms

Here are some of the most common machine learning algorithms:

Linear Regression: Used for predicting continuous values.
Logistic Regression: Used for predicting binary outcomes.
Decision Trees: Used for classification and regression tasks.
Random Forest: An ensemble learning method that combines multiple decision trees.
Support Vector Machines (SVM): Used for classification and regression tasks.
Neural Networks: Used for complex pattern recognition and classification tasks.

Resources

For more information on machine learning, check out our Machine Learning Basics guide.