Difference Between Machine Learning and Deep Learning

1. Introduction to ML

– Machine learning involves algorithms learning from data. – Various techniques like regression, clustering, and SVM.

2. Intro to Deep Learning

– Deep learning is a subset of machine learning. – Involves neural networks with multiple layers.

3. Data Representation

– Machine learning uses handcrafted features. – Deep learning learns features automatically.

4. Model Complexity

– Machine learning models are simpler. – Deep learning models are complex and layered.

5. Feature Engineering

– Machine learning requires manual feature engineering. – Deep learning automates feature extraction.

6. Performance

– Machine learning performs well with structured data. – Deep learning excels with unstructured data.

7. Training Data

– Machine learning requires less data for training. – Deep learning demands large datasets.

8. Hardware Requirements

– Machine learning can run on standard hardware. – Deep learning benefits from GPU acceleration.

9. Application Areas

– Machine learning used in traditional tasks. – Deep learning dominates in image and speech recognition.

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