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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...
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...
Probability and Statistics for Computer Scientists
Probability and Statistics for Computer Scientists

Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools
Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic
...

Learn Blockchain Programming with JavaScript: Build your very own Blockchain and decentralized network with JavaScript and Node.js
Learn Blockchain Programming with JavaScript: Build your very own Blockchain and decentralized network with JavaScript and Node.js

Explore the essentials of blockchain technology with JavaScript to develop highly secure bitcoin-like applications

Key Features

  • Develop bitcoin and blockchain-based cryptocurrencies using JavaScript
  • Create secure and high-performant blockchain networks
  • ...
Deep Learning with Swift for TensorFlow: Differentiable Programming with Swift
Deep Learning with Swift for TensorFlow: Differentiable Programming with Swift

About this book

Discover more insight about deep learning algorithms with Swift for TensorFlow. The Swift language was designed by Apple for optimized performance and development whereas TensorFlow library was designed by Google for advanced machine learning research. Swift for TensorFlow is a combination of both...

Blockchain for Enterprise: Build scalable blockchain applications with privacy, interoperability, and permissioned features
Blockchain for Enterprise: Build scalable blockchain applications with privacy, interoperability, and permissioned features

Implement blockchain principles in your choice of domain using Ethereum

Key Features

  • Build permissioned enterprise-grade blockchain applications from scratch
  • Implement Blockchain-as-a-Service to enterprises in terms of deployment and security
  • Achieve...
Blockchain for Business 2019: A user-friendly introduction to blockchain technology and its business applications
Blockchain for Business 2019: A user-friendly introduction to blockchain technology and its business applications

Your one-stop guide to blockchain technology and its business applications

Key Features

  • Assimilate blockchain services such as Ethereum and Hyperledger to transform industrial applications
  • Know in and out of blockchain technology to understand various business use...
Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning
Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural...

Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras

Explore various Generative Adversarial Network architectures using the Python ecosystem

Key Features

  • Use different datasets to build advanced projects in the Generative Adversarial Network domain
  • Implement projects ranging from generating 3D shapes to a face aging...
Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python
Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python
The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks) dealing not only with images and the use of computers, but also their applications to visualization tasks...
Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field.

...
Modeling and Simulation of Systems Using MATLAB and Simulink
Modeling and Simulation of Systems Using MATLAB and Simulink

Not only do modeling and simulation help provide a better understanding of how real-world systems function, they also enable us to predict system behavior before a system is actually built and analyze systems accurately under varying operating conditions. Modeling and Simulation of Systems Using MATLAB® and...

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