What is the main difference between machine learning and deep learning?
Deep learning is suitable for complex tasks, while machine learning is for basic tasks
Explanation:
The main difference is that Deep Learning uses multi-layer neural networks to handle complex patterns, while traditional Machine Learning is often used for simpler tasks and usually requires manual feature engineering.
Examples:
- Deep Learning: Image recognition, speech recognition, self-driving cars, natural language processing
- Machine Learning: Spam filtering, credit scoring, basic predictions
Why not the others?
- a) Machine learning uses more hidden layers → Incorrect; Deep Learning uses multiple hidden layers.
- b) Deep learning requires less data → Incorrect; Deep Learning usually requires large amounts of data.
- d) Machine learning does not involve feature engineering → Incorrect; Machine Learning often requires manual feature engineering.
