|
Get up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch, you'll get familiarized with tensors, a type of data structure used to calculate arithmetic operations and also learn how they operate. You will then take a look at probability distributions using PyTorch and get acquainted with its concepts. Further you will dive into transformations and graph computations with PyTorch. Along the way you will take a look at common issues faced with neural network implementation and tensor differentiation, and get the best solutions for them.
Moving on to algorithms; you will learn how PyTorch works with supervised and unsupervised algorithms. You will see how convolutional neural networks, deep neural networks, and recurrent neural networks work using PyTorch. In conclusion you will get acquainted with natural language processing and text processing using PyTorch.
What You Will Learn
-
Master tensor operations for dynamic graph-based calculations using PyTorch
-
Create PyTorch transformations and graph computations for neural networks
-
Carry out supervised and unsupervised learning using PyTorch
-
Work with deep learning algorithms such as CNN and RNN
-
Build LSTM models in PyTorch
-
Use PyTorch for text processing
Who This Book Is For
Readers wanting to dive straight into programming PyTorch.
|
|
|
 C++/CLI: The Visual C++ Language for .NETC++/CLI: The Visual C++ Language for .NET introduces Microsoft's new extensions to the C++ syntax that allow you to target the common language runtimethe key to the heart of the .NET 3.0 platform. In 12 no-fluff chapters, Microsoft insider Gordon Hogenson takes you into the core of the C++/CLI language and explains both how the language... |  | Machine Learning and Robot Perception (Studies in Computational Intelligence)This book presents some of the most recent research results in the area of machine learning and robot perception. The book contains eight chapters.
Relevant progress has been done, within the Robotics field, in mechanical systems, actuators, control and planning. This fact, allows a wide application of industrial robots, where... | | |
| | | | Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more
Take your NLP knowledge to the next level and become an AI language understanding expert by mastering the quantum leap of Transformer neural network models
Key Features
-
Build and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using...
|
|
