Softmax function

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Related lectures (30)

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Optimization in Machine Learning

Explores optimization techniques, word embeddings, and recommendation systems in machine learning.

Neural Network: Random Features and Kernel Regression

Covers random features in neural networks and kernel regression equivalence.

Statistical Approach: Summary and Quiz

Discusses statistical view of neural networks, classification tasks, and cross-entropy loss functions.

Adversarial Training: Optimization and Applications

Explores adversarial training optimization, practical implementation, interpretability, fairness, Wasserstein distance, and Wasserstein GANs.

Transformer Architecture: The X Gomega

Delves into the Transformer architecture, self-attention, and training strategies for machine translation and image recognition.

Logistic Regression: Vegetation Prediction

Explores logistic regression for predicting vegetation proportions in the Amazon region through remote sensing data analysis.

Interpreting Output as Probability

Delves into interpreting neural network output as probabilities based on the cross-entropy error function.

Regularized Cross-Entropy Risk

Explores the regularized cross-entropy risk in neural networks, covering training processes and challenges in deep networks.

Neural Networks: Multi-layers

Explains the learning process in multi-layer neural networks, including back-propagation, activation functions, weights update, and error backpropagation.

Linear and Logistic Regression

Covers linear and logistic regression, including underfitting, overfitting, and performance metrics.