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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...
fastText Quick Start Guide: Get started with Facebook's library for text representation and classification
fastText Quick Start Guide: Get started with Facebook's library for text representation and classification

Perform efficient fast text representation and classification with Facebook's fastText library

Key Features

  • Introduction to Facebook's fastText library for NLP
  • Perform efficient word representations, sentence classification, vector representation
  • ...
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...
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...
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...
Python Data Analytics: With Pandas, NumPy, and Matplotlib
Python Data Analytics: With Pandas, NumPy, and Matplotlib
Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. 

This revision is fully updated with new content on social media data analysis, image
...
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...
Mastering Regular Expressions, Second Edition
Mastering Regular Expressions, Second Edition

This book is about a powerful tool called "regular expressions". It teaches you how to use regular expressions to solve problems and get the most out of tools and languages that provide them. Most documentation that mentions regular expressions doesn't even begin to hint at their power, but this book is about ...

Programming in the .NET Environment
Programming in the .NET Environment

Programming in the .NET Environment is the software developer's guide to the .NET Framework. The authors describe Microsoft's vision for distributed component-based systems development and then show programmers how to develop software that takes full advantage of the features of the .NET...

Mastering Regular Expressions
Mastering Regular Expressions
This book is about a powerful tool called "regular expressions."

Here, you will learn how to use regular expressions to solve problems and get the most out of tools that provide them. Not only that, but much more: this book is about mastering regular expressions.

If you use a computer, you can benefit from regular
...
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