PhD degree: Biodiversity in Agriculture and Forestry - Summer Lectures – 17-18 July 2024
Hosted by Prof. Dr. Riccardo Lo Bianco
- “Introduction to machine learning, terminology, types of machine learning, what “learning” means, intuitive understanding of the gradient descent algorithm” – 09:30 – 10:30
- “Model validation“ – 10:30 – 11:10
- Pause – 11:10 – 11:30
- “Unbalanced Datasets and Metrics” 11:30 – 12:30
- “Introduction to Neural Networks” - 09:30 – 10:30
- Pause – 10:30 – 10:50
- “Introduction to Python, Jupyter Notebooks, development environments, best practices, etc.” – 10:50 – 11:30
- “Application of machine learning to food quality control: examples for olive oil, maize and wine” 11:30 – 12:30
- Introduction to learning: Chapter 1, Michelucci, Umberto. Applied Deep Learning with TensorFlow 2. Springer, Berlin, Germany, 2022.
- Terminology: Chapter 2, Michelucci, Umberto. Fundamental Mathematical Concepts for Machine Learning in Science. Springer, 2024.
- Gradient Descent: Section 3.9, Michelucci, Umberto. Fundamental Mathematical Concepts for Machine Learning in Science. Springer, 2024.
- Model Validation: Chapter 7, Michelucci, Umberto. Fundamental Mathematical Concepts for Machine Learning in Science. Springer, 2024.
- Unbalanced Datasets: Chapter 8, Michelucci, Umberto. Fundamental Mathematical Concepts for Machine Learning in Science. Springer, 2024.
- Introduction to Neural Networks: Chapter 1, Michelucci, Umberto. Applied Deep Learning with TensorFlow 2. Springer, Berlin, Germany, 2022.
- An introduction to Keras: Appendix A, Michelucci, Umberto. Applied Deep Learning with TensorFlow 2. Springer, Berlin, Germany, 2022.