General Information
Objective: Study of the main deep learning methods and their applications.
Syllabus: Machine learning basics; Deep Feedforward Networks; Convolutional Neural Networks (CNN), Recurrent Neural Networks; Segmentation and Object Recognition; Frameworks for deep learning and Practical Aspects; Applications of deep learning models for real-world problems.
Duration: 60 hours (19 weeks).
Time: Tuesdays (17:50 - 21:10) - synchronous (SYN) and asynchronous (ASYN) classes.
Grade: Assignments (50%) and Final Project (50%).
Lecturer: André Eugenio Lazzaretti and Heitor Silvério Lopes.
Collaborators (PhD students): Andrei Inácio, Matheus Gutoski, Anderson Brilhador.
Bibliography and Support Materials
Books:
Goodfellow, I., Bengio, Y., Courville, A. Deep Learning. MIT Press, 2016.
Chollet, F., Deep Learning with Python. Manning, 2018
Raschka, S. Python Machine Learning. Packt, 2020
Other Courses:
Andrew Ng at Coursera.
Sebastian Raschka at UW Madison.
Fei Fei Li et al. at Stanford (most similar).
Introduction to Deep Learning at MIT.
Week 1 - 16/08
Content:
(SYN) General overview and Rules.
DERLEI, LUIGI, MATEO, LEONARDO, ANGELO, LEONARDO AUGUSTINHO
Week 1 (15/08): Predicting Continuous Target Variables with Regression Analysis (ASYN)
Week 2, 3, and 4 (22/08, 29/08 and 05/09): Assignment - Regression (ASYN)
Guide (link).
Week 5 (12/09): Working with Unlabeled Data – Clustering Analysis (ASYN)
Week 6 (19/09): Assignment - Clustering (ASYN)
Guide (link).
Week 7 (26/09) - EVENTO DAELN
Não haverá aula!
Week 8 (03/10) - Assignment - Clustering cont. (ASYN)
Guide (link).
ANTONIO, ITALO, VICTOR HUGO, EDUARDO, GUILHERME, MARIO, MATHEUS, MELISSA
Preliminary content (watch the content you need to reinforce your knowledge):
Python:
Mathematical Background:
Week 1 (15/08) - Training Simple Machine Learning Algorithms (ASYN)
Week 2 (22/08) - A Tour of Machine Learning Classifiers Using scikit-learn (ASYN)
Slides (link);
Codes (link);
Complementary material for Scikit-learn: link (Part II - L05);
Similar material in portuguese: link.
Week 3 (29/08) - Building Good Training Sets - Data Preprocessing (ASYN)
Week 4 (05/09) - Compressing Data via Dimensionality Reduction (ASYN)
Week 5 (12/09) - Python and Machine Learning Basics (ASYN)
Guide (link).
Week 6 (19/09) - Learning Best Practices for Model Evaluation and Hyperparameter Tuning (ASYN)
Week 7 (26/09) - EVENTO DAELN
Não haverá aula!
Week 8 (03/10) - Classification with scikit-learn (ASYN)
Guide (link).
Week 9 to 19 - 10/10 to 19/12 - in sync with Deep Learning Course - CPGEI
Check here.