Data science case study for battery data, obtained from RWTH Aachen data repository. The workflow includes problem definition, exploratory analysis and implementation of a predictive model for battery state of charge. This project has been carried out in approximately 2-3 days.
The stack is set up on a 64-bit MacOs11 desktop with Conda 4.9.2 and Python 3.7.6. A new environment is created and activated via terminal. To recreate:
- Clone the project Git repository.
- Create a conda environment for the project from within the project's root directory:
conda env create --force -f environment.yml -n battery
conda activate battery
The "main.py" script executes the whole workflow and saves the output as a logfile in data/output. Total execution time is around 10 mins.
python main.py
- Problem definition and exploratory data analysis.
- Data preprocessing (outliers, scaling) and feature engineering.
- Spot checking various linear and non-linear regression models to choose the best.
- Model fitting, tuning and evaluation of a Random Forest learner on the test dataset.
- Model achieved a train RMSE of 3.0 and test RMSE of 3.7, which is better than the naive baseline of 32 (mean prediction).
├── main.py <- Main python file for execution.
│
├── exploration.ipynb <- Jupyter Notebook to perform exploratory analysis, feature engineering,
| model selection, parameter tuning and validation.
│
├── model <- Trained and serialized RF model.
│
│
├── data
│ ├── raw <- The original, immutable data dump.
│ ├── processed <- Processed dataset.
│ ├── output <- Predicted output with true labels.
│
├── source
│ ├── Requirements.txt <- Required Python packages.
│ ├── fileRead.py <- Input fixtures for pytests.
│ ├── preProcessing.py <- Module containing pytest function for main.py.
│ ├── modelling.py <- Module containing pytest for ranker model.
│ └── prediction.py <- Module containing pytest for remote data retrieving.
│
├── environment.yml <- Required Python packages (refers to Requirements.txt).
├── Makefile <- Makefile to control the project.
├── README.md <- The top-level README for users.
├── setup.py <- Module with the package install script.
│
├── logs
│ ├── logfile<timestamp>.log <- Log of the executions.
│
├── .gitignore <- Files to be ignored by git.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent