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 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
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Build and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using...
| | PyTorch Recipes: A Problem-Solution Approach
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 ... | | |
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Encyclopedia of Parallel Computing (Springer Reference)
Parallelism, the capability of a computer to execute operations concurrently, has been a constant throughout the
history of computing. It impacts hardware, software, theory, and applications. The fastest machines of the past few
decades, the supercomputers, owe their performance advantage to parallelism. Today, physical limitations... | | Water Dynamics in Plant Production
The source of life is water. Life began in the
oceans, which represent the largest stock of water
on Earth. Much less water is stored below the land
surface in the form of fresh groundwater, amounting
to not quite 0.8% of the earth’s total water
reserves, while lakes and rivers combined only
contribute a further... | | Vision in 3D Environments
Seeing in 3D is a fundamental problem for anyorganism or device that
has to operate in the real world. Answering questions such as “how far away
is that?” or “can we fit through that opening?” requires perceiving and making
judgments about the size of objects in three dimensions. So how do we see
in... |
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