Technical requirements
You will need the following Python packages for the example walkthrough:
- Matplotlib: A plotting library for creating data visualizations
- NumPy: An open source library that provides mathematical functions when working with arrays
- pandas: A library that offers data analysis and manipulation tools
- Imbalanced-learn: An open source library imported as
imblearn
that provides tools to handle imbalanced datasets - MXNet: An open source deep learning framework
- TensorFlow: An open source framework for building deep learning applications
- AutoGluon: An open source AutoML library that automates machine learning (ML) tasks
- Cleanlab: An open source library that automatically detects anomalies and finds data errors in a text dataset
- SciPy: An open source Python library for scientific computing
- SciKeras: Provides scikit-learn compatible wrappers for Keras models
- Transformers: Provides pre-trained models for ML tasks
- Scikit-learn...