In part II, we will go through a case study to demonstrate how to use surrogate models in practice. The roadmap for this case study is shown below
In part I of this series, we’ve introduced the idea of using surrogate models to accelerate simulation-based product design processes. This is achieved by training a statistical model to serve as a cheap yet accurate _surrogate _to the simulations in performing various design tasks, therefore significantly improving the analysis efficiency.
In part II, we will go through a case study to demonstrate how to use surrogate models in practice. The roadmap for this case study is shown below:
We will start by introducing the problem's physical background, followed by applying the surrogate modeling technique to the problem. Finally, we will illustrate how to use the trained surrogate model to perform two types of analysis.
In part III of this series, we will briefly discuss some advanced concepts to enhance surrogate modeling capability further.
Let’s get started!
Learning is a new fun in the field of Machine Learning and Data Science. In this article, we’ll be discussing 15 machine learning and data science projects.
Analysis, Price Modeling and Prediction: AirBnB Data for Seattle. A detailed overview of AirBnB’s Seattle data analysis using Data Engineering & Machine Learning techniques.
Applied Data Analysis in Python Machine learning and Data science, we will investigate the use of scikit-learn for machine learning to discover things about whatever data may come across your desk.
Data Preparation Techniques and Its Importance in Machine Learning. “Data are just summaries of thousands of stories, tell a few of those stories to help make the data meaningful.”
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant