Mastering PyTorch, Second Edition

This is the code repository for the book Mastering PyTorch, Second Edition, published by Packt.

What is this book about?

PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch deep learning book will help you uncover expert techniques to get the most out of your data and build complex neural network models.

What you will learn

Implement text, vision, and music generation models using PyTorch
Build a deep Q-network (DQN) model in PyTorch
Deploy PyTorch models on mobile devices (Android and iOS)
Become well versed in rapid prototyping using PyTorch with fastai
Perform neural architecture search effectively using AutoML
Easily interpret machine learning models using Captum
Design ResNets, LSTMs, and graph neural networks (GNNs)
Create language and vision transformer models using Hugging Face

Who This Book Is for?

This deep learning with PyTorch book is for data scientists, machine learning engineers, machine learning researchers, and deep learning practitioners looking to implement advanced deep learning models using PyTorch. This book is ideal for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep learning with Python is required.

Notebooks in each chapter

You can run the notebooks directly from the table below:

Chapter no.	Chapter title	Notebook/Utility Script (GitHub)
1	Overview of Deep Learning Using PyTorch	mnist_pytorch.ipynb
		mnist_tensorflow.ipynb
2	Deep CNN Architectures	DenseNetBlock.ipynb
		GoogLeNet.ipynb
		ResNetBlock.ipynb
		lenet.ipynb
		transfer_learning_alexnet.ipynb
		vgg13_pretrained_run_inference.ipynb
3	Combining CNNs and LSTMs	image_captioning_pytorch.ipynb
4	Deep Recurrent Model Architectures	lstm.ipynb
		rnn.ipynb
5	Advanced Hybrid Models	out_of_the_box_transformers.ipynb
		rand_wire_nn.ipynb
		transformer.ipynb
6	Graph Neural Networks	GNN.ipynb
7	Music and Text Generation with PyTorch	music_generation.ipynb
		text_generation.ipynb
		text_generation_out_of_the_box.ipynb
		text_generation_out_of_the_box_gpt3.ipynb
8	Neural Style Transfer	neural_style_transfer.ipynb
9	Deep Convolutional GANs	dcgan.ipynb
		pix2pix_architecture.ipynb
10	Image Generation Using Diffusion	image_generation_using_diffusion.ipynb
		taj_mahal_image.ipynb
		text_to_image_generation_using_stable_diffusion_v1_5.ipynb
11	Deep Reinforcement Learning	pong.ipynb
13	Operationalizing PyTorch Models into Production	mnist_pytorch.ipynb
		model_scripting.ipynb
		model_tracing.ipynb
		onnx.ipynb
		run_inference.ipynb
15	Rapid Prototyping with PyTorch	fastai.ipynb
		poutyne.ipynb
		pytorch_lightning.ipynb
		pytorch_profiler.ipynb
16	PyTorch and AutoML	automl-pytorch.ipynb
		optuna_pytorch.ipynb
17	PyTorch and Explainable AI	captum_interpretability.ipynb
		pytorch_interpretability.ipynb
18	Recommendation Systems with PyTorch	torch-recsys.ipynb
19	PyTorch and Hugging Face	HuggingFaceAccelerate.ipynb
		HuggingFaceDatasets.ipynb
		HuggingFaceHub.ipynb
		HuggingFaceOptimum.ipynb
		HuggingFacePyTorch.ipynb

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Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost. Simply click on the link to claim your free PDF. Free-Ebook

We also provide a PDF file that has color images of the screenshots/diagrams used in this book at GraphicBundle

Get to know the Author

Ashish Ranjan Jha studied electrical engineering at IIT Roorkee, computer science at École Polytechnique Fédérale de Lausanne (EPFL), and he also completed his MBA at Quantic School of Business, with a distinction in all three degrees. He has worked for bigger tech companies like Oracle and Sony, and recent tech unicorns – Revolut and Tractable, in the fields of data science, machine learning and artificial intelligence. He currently works as head of ML and AI at XYZ Reality, based in London (a construction tech start-up where construction meets AR/VR meets ML/AI to enable real-time data driven construction intelligence). He is also an advisor to SUIND, an agritech startup that uses drones for intelligence. Along with that, he has also authored a book, Fight Fraud with Machine Learning.

asamarah1/MasteringPyTorchV2