Difference between Machine Learning and Deep Learning
Difference between Machine Learning and Deep Learning
The terms Machine Learning (ML) and Deep Learning (DL) are often used interchangeably, but they represent distinct concepts within the field of artificial intelligence (AI). Both play a crucial role in helping machines learn from data and make intelligent decisions, yet they differ in their methodologies, complexity, and applications.
What is Machine Learning?
Machine Learning is a subset of AI that enables systems to learn from data without being explicitly programmed. It focuses on developing algorithms to analyze data, identify patterns, and make predictions or decisions.
Key Features of Machine Learning:
- <span times="" new="" roman";mso-bidi-font-family:="" calibri;mso-bidi-theme-font:minor-latin"="" style="box-sizing: border-box; font-size: 14pt; line-height: 21.4667px;">Requires structured data.
- <span times="" new="" roman";mso-bidi-font-family:="" calibri;mso-bidi-theme-font:minor-latin"="" style="box-sizing: border-box; font-size: 14pt; line-height: 21.4667px;">Relies on feature extraction, where humans manually select the input features for models.
- <span times="" new="" roman";mso-bidi-font-family:="" calibri;mso-bidi-theme-font:minor-latin"="" style="box-sizing: border-box; font-size: 14pt; line-height: 21.4667px;">Standard algorithms include decision trees, support vector machines (SVM), and random forests.
- <span times="" new="" roman";mso-bidi-font-family:="" calibri;mso-bidi-theme-font:minor-latin"="" style="box-sizing: border-box; font-size: 14pt; line-height: 21.4667px;">Applications: Email spam detection, recommendation systems, and fraud detection.
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