Laboratory


Practice Classes


Introduction / Instructions (15/08)

Basic concepts of Machine Learning (ML) (22/08)

Neural Networks / Fundamentals (29/08)

The modular approach for designing NNs (05/09)

Training practices and Tensorflow (12/09)

Supervised applications (19/09)

Optimization and stability (26/09)

Unsupervised Learning (03/10)

Generative Modeling I (10/10)

Generative Modeling II (17/10) 

Tensor Flow (24/10) 


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