When we model the weather situation, there are some differences from the common workflow. In machine learning workflow, here is the general processes: To collect historical data and validation data, create the architecture of the model, train the model, evaluation and improvement, and deploy to an operational application. Due to the specialty of the weather… Continue reading The Specialties of a Machine Learning Workflow in Weather Domain
Tag: machine learning
Weather Opinion: Different people may have different perspectives to differentiate the same weather
Two weeks ago, I had a presentation at TGA 2022 (Taiwan Geoscience Assembly) & Conference on Weather Analysis and Forecasting. The title was "Use Machine Learning to Classify Weather Opinions from WhatsApp Group: A Model Design and Evaluation for Raining Event Prediction". The term "Weather Opinion" is created for this research since the voice from… Continue reading Weather Opinion: Different people may have different perspectives to differentiate the same weather
RL Model Development Processes
Reinforcement learning (RL) is a branch of machine learning. As the word “reinforcement” saying, RL machine (agent) learns from the experiences. When the machine gets positive feedback from certain action to the environment, it will encourage the machine do the same action next time, vice versa. This post is talking about the processes, tips, and… Continue reading RL Model Development Processes
DVC and MLFlow for Creating a ML Pipeline
ML Pipeline When a machine learning (ML) project is scaled up, we may try different algorithms to improve the performance and serve different applications. In these process, some of processes might the same, such as data preprocessing for certain data source, and some are different, such as training algorithms. So we want to modularize different… Continue reading DVC and MLFlow for Creating a ML Pipeline