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Zoekresultaten (21)

HBO/WO

MBO

22 oktober 2024

Calculating vegetation indices from UAV cameras

This video explains how information on crop health can be derived from UAV images by calculating vegetation indices.

Video

lammert.kooistra@wur.nl

2024

VirtualShip software and documentation

This documentation introduces the VirtualShip python package and explains how to install and start using it.

Website

Emma Daniels, Erik van Sebille, Jamie Atkins

23 augustus 2023

Tutorial: Model Evaluation

Learners understand the concept of expected predictive performance and generalization Learners understand the concept of model complexity and its relationship with generalization performance Learners are familiar with bias and variance their relationship with underfitting and overfitting Learners have a firm grasp on evaluating binary classification models with the most widely applied metrics

Website

HCAIM Consortium

23 augustus 2023

Lecture: Decision Theory

The learner gets acquainted with non-quantitative and quantitative approaches to ethics students can define and calculate optimal decisions using univariate distributions and utility/loss functions students can know the elements of decision networks: stochastic/action/utility nodes students can know and apply Bayes' rule (multivariate) students can construct a Naive Bayesian Network (NBN) model students can expand NBN to an NBN-based decision network students can calculate the value of perfect information

Website

HCAIM Consortium

23 augustus 2023

Lecture: Model Compression - Edge Computing

Understand the concept of model compression Provide the rationale behind the techniques of pruning, quantization and knowledge distillation Prepare for understanding of basic implementations using a high-level framework like TensorFlow

Website

HCAIM Consortium

23 augustus 2023

Practical: Model Compression - Edge Computing

Understand how to implement techniques of model compression Grasp the advantages of pruning, quantization and knowledge distillation Becoming familiar with a high-level framework like TensorFlow

Website

HCAIM Consortium

16 augustus 2023

Becerro Galicano Digital

Published by the University of the Basque Country, the Becerro Galicano Digital project provides a digital edition, facsimile, and downloadable data derived from the cartulary. The Becerro Galicano is an extensive cartulary from the monastery of San Millan de la Cogolla, which is situated in the Rioja area on the border between Navarre and Castille. The monastery played a large role in the history of large swathes of northern-central Spain (Navarre, Rioja, Basque Country, Castile), and the Becerro is one of the most important sources for the region’s history from the 8th century to the 13th century. The digital project provides an image of each folio of the manuscript in addition to an accompanying critical text. The website also makes available a bibliography on the cartulary as well as a brief introduction to its importance. Data from the project, including the critical text and indices of names and places, can be downloaded in RTF and TEI format. The website is available in Spanish, English, and Basque.

Website

Fernando García Andreva, David Peterson

11 augustus 2023

Doing the literature review: Selecting databases

Selecting databases You have to decide which databases you will use in your literature search. To limit location bias, you have to use more than one database. Make an informed choice! In this module we list some database features you can take into account. What about Google Scholar? Google Scholar indexes websites with scholarly articles – including websites of academic publishers, university repositories and personal websites of researchers. Related.

Website

Erasmus University Library

2023

Lecture Notes chapter 2: Introduction to Python Programming

This "Maker Lab" course uses Jupyter Notebook files and the Python programming language for data analysis and visualization and uncertainty analysis. Chapter 2 of the lecture notes introduces the Python programming language. It consists of four sub-chapters, each published as separate files. Note: If you do not (yet) have Jupyter Notebook, you cannot fully utilize these .ipynb files. But the attached PDFs will give an idea of their content and functionality. Note also: In order to interact with and fully utilize the Jupyter Notebook documents (including their hyperlinks and pointers to data and image files), it is helpful to save the entire collection locally in a way that preserves the original directory structure. This is easiest to accomplish by downloading all files at once via the JupyterPython-materials zip file and unpacking it (extracting the files) to your preferred local directory. This zip file of all Jupyter Notebook materials is located here: https://search.edusources.nl/materialen/d144774e-9705-489a-b3cd-28e3618f7324

Document

Forrest Bradbury

2023

Maker Lab Assignment: Programming and Data Analysis: Python Exercises

Before the Maker Lab students begin the open inquiry phases, they first learn and practice some important skills, supported by small assignments. In this assignment they are tasked with using a worksheet in Jupyter Notebook and the Python programming language for data analysis and visualization and uncertainty analysis of a provided data set. The analyzed data set is generated quickly via an online survey completed by all students. Note: If you do not (yet) have Jupyter Notebook, you cannot fully utilize the .ipynb file. But the attached PDF will give an idea of its content and functionality. Contents: student worksheet in Jupyter Notebook: Programming-and-DataAnalysis_Python-Exercises.ipynb (and .pdf) instructor link to Google Forms survey for data collection: https://docs.google.com/forms/d/e/1FAIpQLSfWsdadhq-v3ubt1p3EIkzxAVyAyQ-1hBYst_RodV7PEp9E7A/viewform?usp=sharing example of data file: example_Data_Collection_For_Python_Exercises.csv

Document

Forrest Bradbury