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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
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...
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...
Machine Learning and Robot Perception (Studies in Computational Intelligence)
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
...
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...
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...
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems.

Key Features

  • Explore deep reinforcement learning (RL), from the first principles to the latest algorithms
  • Evaluate high-profile RL methods, including value...
Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7
Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality.

Key Features

  • Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and...
Modeling and Tools for Network Simulation
Modeling and Tools for Network Simulation

A crucial step during the design and engineering of communication systems is the estimation of their performance and behavior; especially for mathematically complex or highly dynamic systems network simulation is particularly useful. This book focuses on tools, modeling principles and state-of-the art models for discrete-event based network...

Maximum Linux Security: A Hacker's Guide to Protecting Your Linux Server and Workstation
Maximum Linux Security: A Hacker's Guide to Protecting Your Linux Server and Workstation

Maximum Linux Security: A Hacker's Guide to Protecting Your Linux Server and Workstation is designed for system administrators, managers, or Linux users who wish to protect their Linux servers and workstations from unauthorized intrusions and other external threats to their systems' integrity. Written by an experienced hacker--someone...

Programming Windows Identity Foundation (Dev - Pro)
Programming Windows Identity Foundation (Dev - Pro)

A few years ago, I was sitting at a table playing a game of poker with a few colleagues from Microsoft who had all been involved at various times in the development of Web Services Enhancements for Microsoft .NET (WSE). Don Box, Mark Fussell, Kirill Gavrylyuk, and I played the hands while showman extraordinaire Doug Purdy engaged us with...

Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems (Embedded Systems)
Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems (Embedded Systems)

For real-time systems, the worst-case execution time (WCET) is the key objective to be considered. Traditionally, code for real-time systems is generated without taking this objective into account and the WCET is computed only after code generation. Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems presents...

Standard for VHDL Register Transfer Level (Rtl) Synthesis
Standard for VHDL Register Transfer Level (Rtl) Synthesis

[This introduction is not part of IEEE Std 1076.6-1999, IEEE Standard for VHDL Register Transfer Level (RTL) Synthesis.]

This standard describes a syntax and semantics for VHDL RTL synthesis. It defines the subset of IEEE Std 1076-1993 (VHDL) that is suitable for RTL synthesis as well as the semantics of that subset for the...

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