Ricardo Rodríguez Jorge, PhD
Research Scientist
Department of TICS

Technological Centre Ceit/“Researching Today, Creating the Future”
Donosti, Spain

Reseach group: Data Analysis and Information Management Group

Research visit. Institution: National Technologic of Mexico / Technological Institute of Ciudad Victoria.
(July 1st – July 31th 2022)

Visiting Professor
Czech Technical University in Prague, Czech Republic
(Dec 2016 -January 2017)

Research visit
Tohoku University, Japan (May- Jul 2011)


I welcome my colleagues and fellow academics to this web site. If you would like to discuss any of my published work, please feel free to contact me. My professional interests are mainly in Engineering and my work today has been focused on signal processing and machine learning to bridge innovative ways in these areas.
I am always looking for industrial and academic collaboration, please do not hesitate to contact me for project collaborations. For more information about my current running projects please visit Research projects.
Institute web page:  Data Analysis and Information Management Group
Call for papers: https://www.rodriguezricardo.net/rodriguezjorgericardo/
Courses: https://www.rodriguezricardo.net/rodriguezjorgericardo/
Research Interest Group: Mechatronics,  Signal Processing, Control and Artificial Neural Networks
Contact Information: E-mail: rrodriguezj@ceit.es, Telephone:943 212 800 / Ext. 2940, Office: 011, Skype: rodriguezri,  Mobile phone:

Machine Learning (Master course)

Course Information:
Course Coordinator : Dr. Ricardo Rodriguez Jorge
Level                      : Master course
Time                      : Wednesday ( )
Location                 : H Building
(All obligations for a successful assessment have to be fulfilled until December 14, 2018)
Lecture Notes:
Week Topics Notes Assignments Due date/
1 Motivation and Applications of Machine Learning download
2 Supervised Learning, Linear Regression, Gradient Descent download    
  Batch Gradient Descent, Stochastic Gradient Descent      
3 The concept of Underfitting and Overfitting, locally waighted regression, Logistic regression, Perceptron download    
4 Newton's Method, General Lineal Models download    
5 Discriminative algorithms. Gaussian Discriminant Analysis download
6 Nonlinear Classifiers, Neural Networks, Support Vector Machine download    
7 Bias/variance Tradeoff, Uniform Convergence Theorem download    
8 Feature selection, Model selection download    
9 Online learning, Bayesian Statistical and Regularization download    
10 The concept of unsupervised learning, K-means clustering algorithm download    
11 Reestrictions on a Covariance Matrix download    
12 Generalization to Continuous States, Discretization, Curse of Dimensionality download    
13 Dynamical Systems, Linear Quadratic Regulation, Linearizing a Nonlinear Model download    
14 Machine Learning for Predition download    
15 Applications of Machine Learning download