Build and Train Neural Network with PyTorch in 15 Minutes with this Wrapper
In this tutorial, we will be learning how to use a PyTorch wrapper, included in the Machine Learning Training Utilities version 1.0.1, to train a PyTorch model. The wrapper supports both TensorFlow and PyTorch implementations, and it helps construct a training pipeline, which saves time for other tasks, such as data preprocessing or model architecture. We will use the MNIST dataset for classification, and we will cover how to download, preprocess, and convert it into batches. We will define a neural network with convolutional neural networks (CNNs), an optimizer, and a loss function. We will also import and use custom objects like DataProvider, Metrics, EarlyStopping, and ModelCheckpoint to handle data loading, accuracy calculation, and tracking the training process. Finally, we will test the model on new data and evaluate its performance. By the end of this tutorial, you will have learned how to develop a smooth and tidy training pipeline in PyTorch!
Text Version Tutorial: https://pylessons.com/pytorch-wrapper
GitHub: https://github.com/pythonlessons/mltu...
pypi: https://pypi.org/project/mltu/
#machinelearning #python #pytorch #opencv #tensorflow