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  • Algorithmic Trading for Beginners

    Your Step-by-Step Path to Automated Investing

    A beginner-friendly guide to algorithmic trading covering market basics, strategy design and backtesting, risk management, and how to build simple Python trading bots, with no prior trading or coding experience requiredKey FeaturesLearn through a step-by-step, beginner-safe path from market fundamentals to a working automated trading botGain hands-on Python experience focused on realistic ... Leer más

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  • Deep Learning Fundamentals in Python

    Master Data Science and Machine Learning with Modern Neural Networks written in Python, Theano, and TensorFlow

    Deep learning is making waves. At the time of this writing (March 2016), Google’s AlghaGo program just beat 9-dan professional Go player Lee Sedol at the game of Go, a Chinese board game. Experts in the field of Artificial Intelligence thought we were 10 years away from achieving a victory against a top professional Go player, but progress seems to have accelerated! While deep learning is a ... Leer más

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    How Technology Is Shaping the New Reality

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  • Computer Vision

    Models, Learning, and Inference

    This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new ... Leer más

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  • Python Deep Learning Cookbook

    Over 75 practical recipes on neural network modeling, reinforcement learning, and transfer learning using Python

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  • Computer-Assisted and Robotic Endoscopy

    Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Revised Selected Papers

    Series series Springer Nature Proceedings Computer Science
    This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Computer Assisted and Robotic Endoscopy, CARE 2015, held in conjunction with MICCAI 2015, in Munich, Germany, in October 2015.The 15 revised full papers were carefully selected out of 20 initial submissions and focus on recent technical advances associated with computer vision; ... Leer más

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  • Machine Learning for OpenCV 4

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  • OpenCV 3 Blueprints

    Expand your knowledge of computer vision by building amazing projects with OpenCV 3

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  • An Introduction to Object Recognition

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    Series series Computer Science (R0)
    Rapid development of computer hardware has enabled usage of automatic object recognition in an increasing number of applications, ranging from industrial image processing to medical applications, as well as tasks triggered by the widespread use of the internet. Each area of application has its specific requirements, and consequently these cannot all be tackled appropriately by a single, general ... Leer más

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  • Image Processing and Pattern Recognition

    Series Libro 5 - Neural Network Systems Techniques and Applications
    Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech classification, medical imaging, paper currency recognition, classification reliability techniques, and sensor technology. The text emphasizes algorithms and architectures for achieving practical and effective systems, and presents many examples. Practitioners, ... Leer más

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  • Dictionary of Computer Vision and Image Processing, Enhanced Edition

    Written by leading researchers, the 2nd Edition of the Dictionary of Computer Vision & Image Processing is a comprehensive and reliable resource which now provides explanations of over 3500 of the most commonly used terms across image processing, computer vision and related fields including machine vision. It offers clear and concise definitions with short examples or mathematical precision where ... Leer más

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  • Discrete-Time Neural Observers

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