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Deep Learning with PyTorch: A practical approach to building neural network models using PyTorch
Deep Learning with PyTorch: A practical approach to building neural network models using PyTorch

Build neural network models in text, vision and advanced analytics using PyTorch

Key Features

  • Learn PyTorch for implementing cutting-edge deep learning algorithms.
  • Train your neural networks for higher speed and flexibility and learn how to implement them in various...
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python
Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras

Key Features

  • Implement machine learning algorithms to build, train, and validate algorithmic models
  • Create your own algorithmic design process to apply...
Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more
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...
Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch
Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by...
PyTorch Recipes: A Problem-Solution Approach
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...
Knowledge-Based Neurocomputing
Knowledge-Based Neurocomputing
Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems can learn and adapt to a changing environment. In knowledge-based...
Natural Computing: 4th International Workshop on Natural Computing
Natural Computing: 4th International Workshop on Natural Computing

The complex behavior of systems in nature is rooted in intricate mechanisms of interaction that often supersede human-made systems in terms of reliability, power efficiency, and computational capacity. Researchers have begun to realize that natural systems are a great source of inspiration for novel algorithms in computation and communication...

Neural Networks with Discontinuous/Impact Activations (Nonlinear Systems and Complexity)
Neural Networks with Discontinuous/Impact Activations (Nonlinear Systems and Complexity)

This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural...

Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering (Water Science and Technology Library)
Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering (Water Science and Technology Library)

“Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important...

JMP 12 Specialized Models
JMP 12 Specialized Models

JMP 12 Specialized Models provides details about modeling techniques such as partitioning, neural networks, nonlinear regression, and time series analysis. Topics include the Gaussian platform, which is useful in analyzing computer simulation experiments. The book also covers the Response Screening platform, which is useful in testing the...

Novel Therapeutic Targets for Antiarrhythmic Drugs
Novel Therapeutic Targets for Antiarrhythmic Drugs

Profiles potential treatment approaches for cardiac arrhythmias

Cardiac arrhythmias of ventricular origin are responsible for the deaths of nearly half a million Americans each year while atrial fibrillation accounts for about 2.3 million cases per year, a rate that is projected to increase 2.5 fold over the next half...

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