Machine Learning II
Aprendizado não supervisionado: modelos generativos (e.g., Generative Adversarial Networks, Normalizing Flows, Variational Autoencoders, Denoising diffusion models), redução de dimensionalidade (e.g., Auto-encoders, Principal Component Analysis, Stochastic Neighborhood Embedding) e aprendizagem de representação (e.g., word2vec, contrastive learning).
Basic Information
Workload
60 hours
Requirements
Machine Learning I
Mandatory:
- Kevin Murpy. Probabilistic Machine Learning: Advanced topics. Aaron Courville, Ian Goodfellow, Yoshua Bengio. Deep Learning. Christopher Bishop. Pattern Analysis and Machine Learning.