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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...
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...
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...
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...
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...
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...
Coherent Behavior in Neuronal Networks (Springer Series in Computational Neuroscience)
Coherent Behavior in Neuronal Networks (Springer Series in Computational Neuroscience)

Recent experimental research advances have led to increasingly detailed descriptions of how networks of interacting neurons process information. With these developments, it has become clear that dynamic network behaviors underlie information processing, and that the observed activity patterns cannot be fully explained by simple concepts such as...

Applying Computational Intelligence: How to Create Value
Applying Computational Intelligence: How to Create Value

The flow of academic ideas in the area of computational intelligence is impacting industrial practice at considerable speed. Practitioners face the challenge of tracking, understanding and applying the latest techniques, which often prove their value even before the underlying theories are fully understood. This book offers realistic guidelines...

Design and Implementation of Data Mining Tools
Design and Implementation of Data Mining Tools

Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors’ own research work, the book takes a practical approach to the...

Advances of Soft Computing in Engineering (CISM International Centre for Mechanical Sciences)
Advances of Soft Computing in Engineering (CISM International Centre for Mechanical Sciences)

The articles in this book present advanced soft methods related to genetic and evolutionary algorithms, immune systems, formulation of deterministic neural networks and Bayesian NN. Many attention is paid to hybrid systems for inverse analysis fusing soft methods and the finite element method. Numerical efficiency of these soft methods is...

Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications
Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications
Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications presents methodologies, architectures, and approaches on experiential automated learning. This critical mass of sought after research assembles the most intriguing and innovative applications, advancements, and leading studies on the...
Mind Design II: Philosophy, Psychology, and Artificial Intelligence
Mind Design II: Philosophy, Psychology, and Artificial Intelligence
"Ming Design II is a welcome update of its predecessor, itself a useful compendium on the philosophy of cognitive science. This new volume retains the intellectual foundations, and some discussions of classical AI built on them, while adding connectionism, situated AI, and dynamic systems theory as extra storeys. Which of these is...
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