Python: Machine Learning, Optimization, and Applications
Python: Machine Learning, Optimization, and Applications
Goals
1. Provide an introduction to the Python programming language and its main modules (Numpy, Scipy and Matplotlib).
2. Introduce, from a theoretical-practical perspective, machine learning techniques of regression, classification and clustering, using the scikit-learn module in Python.
3. Introduce, from a theoretical-practical perspective, metaheuristic optimization techniques based on path and population, using the DEAP module in Python.
4. Introduce deep learning techniques from a theoretical-practical perspective, including Fully Connected Networks, Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).
5. Introduction to reinforcement learning and deep reinforcement learning.
6. Commercial applications.
Skills
- Ability to solve problems with initiative, decision-making, creativity, and to communicate and transmit knowledge, skills and abilities.
- Ability to recognize when information is needed, where to locate it, how to assess its suitability, and use it appropriately according to the problem at hand.
- That students know how to apply the knowledge acquired and their problem-solving skills in new or unfamiliar environments within broader (or multidisciplinary) contexts.
- That students possess the learning skills that will allow them to continue studying in a way that will be largely self-directed or autonomous.
Evaluation Procedures:
Attendance, Tests, Assignments
Requirements
Specific admission requirements for the studies : Graduates and Master's and PhD students; also, anyone interested with prior programming knowledge (Python not required).
Student selection criteria: Pre-registration order.
Is a university degree required to access this course? :No.
Address
Promoting Unit: Higher Technical School of Engineering.
Director of studies: Mr. Sergio Luis Toral Marín.
Director's Department: Electronic Engineering.
Delivery
Language of instruction: Spanish.
Location: Higher Technical School of Engineering (Computing Center).
Information
Phone: 954481293
Email: storal@us.es
