The educational objective of the present course is to bring the student closer to some applications of Artificial Intelligence (AI) and Machine Learning (ML) in the engineering and artistic fields. The course is therefore designed in two parts: the first concerns AI applications to electrical energy and information engineering; the second focuses on the use of ML techniques for musical and artistic production in general. Thus, the student will have the opportunity to learn how AI is a very versatile and performing tool in application fields that are very distant culturally.
scheda docente
materiale didattico
- Introductory notes on algorithms and problem solving from an engineering point of view
- Evolutionary Calculation: Genetic Algorithms, Swarm Intelligence.
- The Neural Networks.
- Programming languages and development environments: python.
2. Application of artificial intelligence in industrial and information engineering
- Application of Evolutionary Calculus for optimization and inverse problems in materials engineering, energy and biomedical fields.
- Neural, genetic and swarm intelligence models applied to the modeling of materials and devices.
- Application of AI and machine learning in design.
3. Applications of AI to music and art in general
- ML techniques for musical composition. How to computerize the musical signal: MIDI.
- Generative artificial intelligence in the visual and literary arts.
Programma
1. Algorithms and artificial intelligence- Introductory notes on algorithms and problem solving from an engineering point of view
- Evolutionary Calculation: Genetic Algorithms, Swarm Intelligence.
- The Neural Networks.
- Programming languages and development environments: python.
2. Application of artificial intelligence in industrial and information engineering
- Application of Evolutionary Calculus for optimization and inverse problems in materials engineering, energy and biomedical fields.
- Neural, genetic and swarm intelligence models applied to the modeling of materials and devices.
- Application of AI and machine learning in design.
3. Applications of AI to music and art in general
- ML techniques for musical composition. How to computerize the musical signal: MIDI.
- Generative artificial intelligence in the visual and literary arts.
Testi Adottati
Zhng, A., Lipton, Z. C., Li, M., & Smola, A. J. (2021). Dive into deep learning. arXiv preprint arXiv:2106.11342. Available online: https://d2l.ai/Bibliografia Di Riferimento
Zhng, A., Lipton, Z. C., Li, M., & Smola, A. J. (2021). Dive into deep learning. arXiv preprint arXiv:2106.11342. Disponibile online: https://d2l.ai/ Intelligenza Artificiale e arte - ISBN-13 978-8816606012 Editore Jaca Book Data di pubblicazione 5 novembre 2020Modalità Erogazione
Face-to-face Course: traditional classroom delivery methodModalità Frequenza
Attendance is strongly recommended.Modalità Valutazione
Discussion of course topics with open questions.
scheda docente
materiale didattico
- Introductory notes on algorithms and problem-solving from an engineering perspective.
- Evolutionary computation: Genetic Algorithms, Swarm Intelligence.
- Neural Networks.
- Programming languages and development environments: Python.
2. Application of Artificial Intelligence in Industrial and Information Engineering
- Application of Evolutionary Computation for optimization and inverse problems in materials engineering, energy, and biomedical fields.
- Neural, genetic, and swarm intelligence models applied to materials and devices modeling.
- Application of AI and machine learning in the field of design process.
3. Applications of AI in Music and Art in General
- Machine Learning techniques for musical composition. Digitizing musical signals: MIDI.
- Generative artificial intelligence in visual and literary arts.
"Artificial Intelligence and Art" - ISBN-13 978-8816606012 Publisher: Jaca Book Publication Date: November 5, 2020
Lecture notes provided by the professor.
Programma
1. Algorithms and Artificial Intelligence- Introductory notes on algorithms and problem-solving from an engineering perspective.
- Evolutionary computation: Genetic Algorithms, Swarm Intelligence.
- Neural Networks.
- Programming languages and development environments: Python.
2. Application of Artificial Intelligence in Industrial and Information Engineering
- Application of Evolutionary Computation for optimization and inverse problems in materials engineering, energy, and biomedical fields.
- Neural, genetic, and swarm intelligence models applied to materials and devices modeling.
- Application of AI and machine learning in the field of design process.
3. Applications of AI in Music and Art in General
- Machine Learning techniques for musical composition. Digitizing musical signals: MIDI.
- Generative artificial intelligence in visual and literary arts.
Testi Adottati
Zhng, A., Lipton, Z. C., Li, M., & Smola, A. J. (2021). "Dive into Deep Learning." arXiv preprint arXiv:2106.11342. Available online: https://d2l.ai/"Artificial Intelligence and Art" - ISBN-13 978-8816606012 Publisher: Jaca Book Publication Date: November 5, 2020
Lecture notes provided by the professor.
Modalità Frequenza
Attendance requiredModalità Valutazione
Evaluation of experimental project and open questions on topics explained during the course