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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...
Quantum Computing for Everyone (The MIT Press)
Quantum Computing for Everyone (The MIT Press)

An accessible introduction to an exciting new area in computation, explaining such topics as qubits, entanglement, and quantum teleportation for the general reader.

Quantum computing is a beautiful fusion of quantum physics and computer science, incorporating some of the most stunning ideas from twentieth-century...

A Century of Electrical Engineering and Computer Science at MIT, 1882-1982
A Century of Electrical Engineering and Computer Science at MIT, 1882-1982

The book's text and many photographs introduce readers to the renowned teachers and researchers who are still well known in engineering circles.

Electrical engineering is a protean profession. Today the field embraces many disciplines that seem far removed from its roots in the telegraph, telephone, electric...

Reaction-Diffusion Automata: Phenomenology, Localisations, Computation (Emergence, Complexity and Computation)
Reaction-Diffusion Automata: Phenomenology, Localisations, Computation (Emergence, Complexity and Computation)

Reaction-diffusion and excitable media are amongst most intriguing substrates. Despite apparent simplicity of the physical processes involved the media exhibit a wide range of amazing patterns: from target and spiral waves to travelling localisations and stationary breathing patterns. These media are at the heart of most natural processes,...

Advances in Mathematical Modeling for Reliability
Advances in Mathematical Modeling for Reliability
Advances in Mathematical Modeling for Reliability discusses fundamental issues on mathematical modeling in reliability theory and its applications. Beginning with an extensive discussion of graphical modeling and Bayesian networks, the focus shifts towards repairable systems: a discussion about how sensitive availability calculations parameter...
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

Handbook of Signal Processing Systems
Handbook of Signal Processing Systems

In this new edition of the Handbook of Signal Processing Systems, many of the chapters from the previous editions have been updated, and several new chapters have been added. The new contributions include chapters on signal processing methods for light field displays, throughput analysis of dataflow graphs, modeling for...

Programming: Principles and Practice Using C++
Programming: Principles and Practice Using C++

An Introduction to Programming by the Inventor of C++

 

Preparation for Programming in the Real World

 

The book assumes that you aim eventually to write...

Deep Belief Nets in C++ and CUDA C: Volume 3: Convolutional Nets
Deep Belief Nets in C++ and CUDA C: Volume 3: Convolutional Nets
Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract...
Beginning Machine Learning in iOS: CoreML Framework
Beginning Machine Learning in iOS: CoreML Framework
Implement machine learning models in your iOS applications. This short work begins by reviewing the primary principals of machine learning and then moves on to discussing more advanced topics, such as CoreML, the framework used to enable machine learning tasks in Apple products. 

Many applications on iPhone use machine
...
Become a Python Data Analyst: Perform exploratory data analysis and gain insight into scientific computing using Python
Become a Python Data Analyst: Perform exploratory data analysis and gain insight into scientific computing using Python

Enhance your data analysis and predictive modeling skills using popular Python tools

Key Features

  • Cover all fundamental libraries for operation and manipulation of Python for data analysis
  • Implement real-world datasets to perform predictive analytics with Python
  • ...
Introduction to Python for Engineers and Scientists: Open Source Solutions for Numerical Computation
Introduction to Python for Engineers and Scientists: Open Source Solutions for Numerical Computation

Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for...

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