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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 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...
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...
Microsoft Windows 2000 Scripting Guide
Microsoft Windows 2000 Scripting Guide

Welcome to the Microsoft® Windows® 2000 Scripting Guide.

As computers and computer networks continue to grow larger and more complex, system administrators continue to face new challenges. Not all that long ago, system administration was limited to managing a...

CCIE Self-Study: CCIE Security Exam Certification Guide, Second Edition
CCIE Self-Study: CCIE Security Exam Certification Guide, Second Edition
The Cisco authorized self-study test preparation guide for CCIE Security 2.0 350-018 written exam The only official, Cisco endorsed study guide for the CCIE Security 2.0 written exam Includes best-of-breed self-assessment series features, including a CD-ROM test engine, "Do I Know This Already?" quizzes, topic lists/foundation...
Cisco Catalyst QoS: Quality of Service in Campus Networks
Cisco Catalyst QoS: Quality of Service in Campus Networks

Quality of service (QoS) is the set of techniques designed to manage network resources. QoS refers to the capability of a network to provide better service to selected network traffic over various LAN and WAN technologies. The primary goal of QoS is to provide flow priority, including dedicated bandwidth, controlled jitter and...

AD HOC NETWORKS: Technologies and Protocols
AD HOC NETWORKS: Technologies and Protocols
Wireless mobile networks and devices are becoming increasingly popular as
they provide users access to information and communication anytime and anywhere.
Conventional wireless mobile communications are usually supported
by a wired fixed infrastructure. A mobile device would use a single-hop wireless
radio communication to...
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...
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