-
We need to work out what we're doing with the data, once we have it
-
# UQ4ML – Uncertainty Quantification Techniques in Machine Learning Models
This session focuses on uncertainty quantification (UQ) techniques in machine learning models and their applications acros…
-
### Description
Wrong file is compiled for online display
### (Optional:) Please add any files, screenshots, or other information here.
_No response_
### (Required) What is this issue most closely…
-
Machine learning models with solved datasets and solutions
-
**Development of Initial Model/Prototype: SDXL-Detector**
The initial phase of the project involved the development of a prototype model, designated as the SDXL-detector. Researched ways through medi…
-
## Motivation
Machine learning models are generally black boxes. These are difficult to explain or get to know the internal workings of. Meanwhile, they often provide state of the art performance in …
-
### Initial request
In preparations to disseminate forecasted tropical cyclone tracks from machine learning models, there is a need to introduce new data subcategories to identify these products.
…
-
Use supervised learning algorithms to train ML models on the data
-
Proposing the development of a house price prediction web app using machine learning and AI technologies.
## Objectives
1. Develop a user-friendly web interface for predicting house prices.
2. Im…
-
could be random forests, boosted regression trees, or similar
would have the benefit of considering interactions among explanatory variables more effectively