Cronograma 2021/03

Preliminary content:

  • Python:

    • General overview: link (Part II - L03 and L04);

      • Similar material in portuguese: link.

  • Mathematical Background:

  • Track on Signals, Images, and Patterns: link.


Complementary material:

  • Machine Learning course using the same book (by Prof. Sebastian Raschka): link.

    • Similar material in portuguese: link.

Schedule:

  • 27/09 - Lecture 0 (dates, grades, etc):

  • 27/09 - Lecture 1 - Introduction:

04/10 - Lecture 2 - Training Simple Machine Learning Algorithms

04/10 - Lecture 3 - A Tour of Machine Learning Classifiers Using scikit-learn

  • Slides (link);

  • Videos (link1, link2, link3);

  • Codes (link);

  • Complementary material for Scikit-learn: link (Part II - L05);

    • Similar material in portuguese: link.

  • More detailed information (advanced material):

18/10 - Lecture 4 - Building Good Training Sets - Data Preprocessing

25/10 - Assignment 1 - Python and Machine Learning Basics

08/11 - Lecture 5 - Compressing Data via Dimensionality Reduction

22/11 - Assignment 2 - Classification with scikit-learn

29/11 - Lecture 6 - Learning Best Practices for Model Evaluation and Hyperparameter Tuning

06/12 - Lecture 7 - Implementing a Multilayer Artificial Neural Network from Scratch

  • Slides (link);

  • Videos (link);

  • Codes (link);

  • More detailed information (advanced material, including Backpropagation): video.

13/12 - Assignment 3 - Real Problem

20/12 - Assignment 4 - Embedded Machine Learning