Part I - Core Pytorch

Chapter	Notebooks
Chapter 1: Introducing Deep Learning and the PyTorch Library	testing.ipynb
Chapter 2: Pretrained Networks	cyclegan.ipynb, pre_trained_networks.ipynb
Chapter 3: It Starts with a Tensor	named_tensors.ipynb, tensors.ipynb
Chapter 4: Real-World Data Representation Using Tensors	image_dog.ipynb, tabular_wine.ipynb, text_jane_austen.ipynb, time_series_bikes.ipynb, volumetric_ct.ipynb
Chapter 5: The Mechanics of Learning	autograd.ipynb, optimizers.ipynb, parameter_estimation.ipynb
Chapter 6: Using a Neural Network to Fit the Data	neural_networks.ipynb
Chapter 7: Telling Bird from Airplanes: Learning from Images	datasets.ipynb, birds_airplanes.ipynb, full_code ipynb
Chapter 8: Using convolutions to generalize	convolutions.ipynb