========= Tutorials ========= .. _tutorials: The following are examples and notebooks on how to use skorch. * `Basic Usage `_ - Explores the basics of the skorch API. `Run in Google Colab 💻 `_ * `MNIST with scikit-learn and skorch `_ - Define and train a simple neural network with PyTorch and use it with skorch. `Run in Google Colab 💻 `_ * `Benchmarks skorch vs pure PyTorch `_ - Compares the performance of skorch and using pure PyTorch on MNIST. * `Transfer Learning with skorch `_ - Train a neural network using transfer learning with skorch. `Run in Google Colab 💻 `_ * `Image Segmentation with UNets `_ - Use transfer learning to train a UNet model for image segmentation. * `Using skorch with Dask `_ - Using Dask to parallelize grid search across GPUs. * `World level language modeling RNN `_ - Uses skorch to train a language model. * `Seq2Seq Translation using skorch `_ - Translation with a seqeuence to sequence network. * `Advanced Usage `_ - Dives deep into the inner works of skorch. `Run in Google Colab 💻 `_ * `Gaussian Processes `_ - Train Gaussian Processes with the help of GPyTorch. `Run in Google Colab 💻 `_ * `Hugging Face Finetunging `_ - Fine-tune a BERT model for text classification with the Hugging Face transformers library and skorch. `Run in Google Colab 💻 `_ * `Hugging Face Vision Transformer `_ - Show how to fine-tune a vision transformer model for a classification task using the Hugging Face transformers library and skorch. `Run in Google Colab 💻 `_ * `SkorchDoctor `_ - Diagnosing problems in training your neural net `Run in Google Colab 💻 `_ * `Classifying with LLMs `_ - Using (Large) Language Models as zero-shot and few-shot classifiers `Run in Google Colab 💻 `_