Artificial Neural Networks and Deep Learning
2. Perceptron
Initializing search
insper/ann-dl
Artificial Neural Networks and Deep Learning
insper/ann-dl
Ementa
Classes
Classes
1. Concepts
2. Data
3. Preprocessing
4. Metrics and Evaluation
4. Metrics and Evaluation
4.1. Classification Metrics
4.2. Regression Metrics
5. Neural Networks
6. Perceptron
7. Multi-Layer Perceptron
8. Optimization
8. Optimization
8.1. Gradient Descent
8.2. SGD
8.3. Momentum
8.4. Adam Optimizer
9. Regularization
9. Regularization
9.1. L1 and L2 Regularization
9.2. Dropout
9.3. Batch Normalization
9.4. Early Stopping
10. Deep Learning
11. Convolutional
12. Generative Models
12. Generative Models
12.1. VAEs
12.2. GANs
12.3. Diffusion Models
References
Versions
Versions
Terms and Conditions
2025.2
2025.2
Presentation
Exercises
Exercises
1. Data
2. Perceptron
3. MLP
4. Metrics
Projects
Projects
1. Classification
2. Regression
3. Generative Models
2. Perceptron
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