Deep Learning
(MO434A/MC934B)

Prof. Alexandre Xavier Falc√£o

January, 1st 2023





Figures and datasets required for the notebooks.
Notebooks used in the lectures.
Instructions to install python environment and packages for this course.

Introduction to Deep Learning
Fundamentals of Neural Networks (Part I - classification x regression)
Fundamentals of Neural Networks (Part II)
Art of Training Deep Neural Networks
Fundamentals of Image Analysis using Deep Learning
Convolutional Neural Networks (image classification)
Applications in Image Analysis (Part I -- object detection and recognition)
Applications in Image Analysis (Part II -- image segmentation)
Introduction To Text Analysis (text preprocessing)
Text Representation (text embedding)
Recurrent Neural Networks (text classification)
Transformers (applications in text analysis and image classification)