data processing and machine learning model for EIS
Project description
Machine Learning on EIS
Project Objectives:
Current Functionality:
Our results are presented in the user interface called echem_pred. This UI has the following functionalities:
- Data visualization:
- EIS plotting
- dqdv
- Battery cycling plotting
- Machine Learning: Our machine learning has two different modes: online training and offline training. Online training includes.... while offline training uses developed....
- Offline data training
- Online data training
- Decision Tree
Modules Overview:
- echem_pred.py: Main file for the user interface. Including three main parts: main window, data visualization (window 2), and machine learning (window 3).
Software Tutorial:
After cloning this repo annd installing the requirements, the Echem Visualizer App can be used to interact the xx functions to visualize cycling data.
To start the app please run....:
After running, the main page should look like this:
Installation:
Environment:
(What's the required environment)
Instruction:
(How to install)
Acknowledgement:
Release history Release notifications | RSS feed
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