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Signal Processing for Remote Sensing
Signal Processing for Remote Sensing
Signal processing has been playing an increasingly important role in remote sensing, though most remote sensing literatures are concerned with remote sensing images. Many data received by remote sensors such as microwave and geophysical sensors, are signals or waveforms, which can be processed by analog and digital signal...
Learn Unity ML-Agents - Fundamentals of Unity Machine Learning: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games
Learn Unity ML-Agents - Fundamentals of Unity Machine Learning: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games

Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity

Key Features

  • Learn how to apply core machine learning concepts to your games with Unity
  • Learn the Fundamentals of Reinforcement Learning and Q-Learning and apply...
Data Algorithms: Recipes for Scaling Up with Hadoop and Spark
Data Algorithms: Recipes for Scaling Up with Hadoop and Spark

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as...

Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents
Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents

A practical guide to mastering reinforcement learning algorithms using Keras

Key Features

  • Build projects across robotics, gaming, and finance fields, putting reinforcement learning (RL) into action
  • Get to grips with Keras and practice on real-world unstructured...
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...
Soft Computing for Business Intelligence (Studies in Computational Intelligence)
Soft Computing for Business Intelligence (Studies in Computational Intelligence)

The book Soft Computing for Business Intelligence is the remarkable output of a program based on the idea of joint trans-disciplinary research as supported by the Eureka Iberoamerica Network and the University of Oldenburg.

It contains twenty-seven papers allocated to three sections: Soft Computing, Business...

Intelligent Mobile Projects with TensorFlow: Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi
Intelligent Mobile Projects with TensorFlow: Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi

Create Deep Learning and Reinforcement Learning apps for multiple platforms with TensorFlow

Key Features

  • Build TensorFlow-powered AI applications for mobile and embedded devices
  • Learn modern AI topics such as computer vision, NLP, and deep reinforcement learning
  • ...
The Handbook of Brain Theory and Neural Networks: Second Edition
The Handbook of Brain Theory and Neural Networks: Second Edition
Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields related to the two great questions: How does the brain work? and, How can we build intelligent machines?

Once
...
Session Initiation Protocol (SIP): Controlling Convergent Networks (McGraw-Hill Communication Series)
Session Initiation Protocol (SIP): Controlling Convergent Networks (McGraw-Hill Communication Series)
Telephone networks have come a long ways in the last 100 years. Or have they? If one looks at how a telephone network works, not much has changed. Connections are still made through “dedicated” circuits connected end to end for the duration of a call. While switchboard operators have been replaced by digital switching systems, the...
Applied Security Visualization
Applied Security Visualization
APPLIED SECURITY VISUALIZATION

 

“Collecting log data is one thing, having relevant information is something else. The art to transform all kinds of log data into meaningful security information is the core of this book. Raffy illustrates in a...

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.

...
Practical Video Game Bots: Automating Game Processes using C++, Python, and AutoIt
Practical Video Game Bots: Automating Game Processes using C++, Python, and AutoIt

Develop and use bots in video gaming to automate game processes and see possible ways to avoid this kind of automation. This book explains how bots can be very helpful in games such as multiplayer online games, both for training your character and for automating repetitious game processes in order to start a competition with human...

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