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Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python

Develop real-world applications powered by the latest advances in intelligent systems

Key Features

  • Gain real-world contextualization using deep learning problems concerning research and application
  • Get to know the best practices to improve and optimize your machine...
R Deep Learning Projects: Master the techniques to design and develop neural network models in R
R Deep Learning Projects: Master the techniques to design and develop neural network models in R

5 real-world projects to help you master deep learning concepts

Key Features

  • Master the different deep learning paradigms and build real-world projects related to text generation, sentiment analysis, fraud detection, and more
  • Get to grips with R's impressive range of...
OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications
OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications

Recipe-based approach to tackle the most common problems in Computer Vision by leveraging the functionality of OpenCV using Python APIs

Key Features

  • Build computer vision applications with OpenCV functionality via Python API
  • Get to grips with image processing, multiple...
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems

Insightful projects to master deep learning and neural network architectures using Python and Keras

Key Features

  • Explore deep learning across computer vision, natural language processing (NLP), and image processing
  • Discover best practices for the training of deep neural...
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem

Key Features

  • Build deep learning models with transfer learning principles in Python
  • implement transfer learning to solve real-world research...
Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs
Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs

Build and deploy powerful neural network models using the latest Java deep learning libraries

Key Features

  • Understand DL with Java by implementing real-world projects
  • Master implementations of various ANN models and build your own DL systems
  • Develop...
Deep Learning Essentials: Your hands-on guide to the fundamentals of deep learning and neural network modeling
Deep Learning Essentials: Your hands-on guide to the fundamentals of deep learning and neural network modeling

Get to grips with the essentials of deep learning by leveraging the power of Python

Key Features

  • Your one-stop solution to get started with the essentials of deep learning and neural network modeling
  • Train different kinds of neural networks to tackle various problems in...
Pro JavaFX 9: A Definitive Guide to Building Desktop, Mobile, and Embedded Java Clients
Pro JavaFX 9: A Definitive Guide to Building Desktop, Mobile, and Embedded Java Clients

At the annual JavaOne conference in May 2007, Sun Microsystems announced a new product family named JavaFX. Its stated purpose includes enabling the development and deployment of content-rich applications on consumer devices such as cell phones, televisions, in-dash car systems, and browsers. Josh Marinacci, a software engineer at Sun, made...

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...
Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL
Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL

Learn how to accelerate C++ programs using data parallelism. This open access book enables C++ programmers to be at the forefront of this exciting and important new development that is helping to push computing to new levels. It is full of practical advice, detailed explanations, and code examples to illustrate key topics. 

...
3D Graphics for Game Programming
3D Graphics for Game Programming
Many of computer graphics classes in colleges are focused on real-time rendering and animation. However, it is not easy to nd an appropriate textbook, which presents the state of the art in interactive graphics, is balanced between theory and practicality, and is of a proper length to be covered in a semester. This book is...
Seven Concurrency Models in Seven Weeks: When Threads Unravel (The Pragmatic Programmers)
Seven Concurrency Models in Seven Weeks: When Threads Unravel (The Pragmatic Programmers)

Your software needs to leverage multiple cores, handle thousands of users and terabytes of data, and continue working in the face of both hardware and software failure. Concurrency and parallelism are the keys, and Seven Concurrency Models in Seven Weeks equips you for this new world. See how emerging technologies such as actors and...

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