ARTIFICIAL INTELIGENCE

Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real-World Performance

Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real-World Performance

Neural Networks in Finance and Investing is a revised and expanded edition of the first book to exclusively address the use of neural networks in the financial arena. Robert Trippi and Efraim Turban have assembled here a stellar collection of articles by recognized experts from industry and academia on this increasingly important subject. They discuss […]

Dark Pools: The Rise of the Machine Traders and the Rigging of the U.S. Stock Market

Dark Pools: The Rise of the Machine Traders and the Rigging of the U.S. Stock Market

A news-breaking account of the global stock market’s subterranean battles, Dark Pools portrays the rise of the “bots”–artificially intelligent systems that execute trades in milliseconds and use the cover of darkness to out-maneuver the humans who’ve created them. In the beginning was Josh Levine, an idealistic programming genius who dreamed of wresting control of the […]

TensorFlow 1.x Deep Learning Cookbook: Over 90 unique recipes to solve artificial-intelligence driven problems with Python

TensorFlow 1.x Deep Learning Cookbook: Over 90 unique recipes to solve artificial-intelligence driven problems with Python

Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x Key Features Skill up and implement tricky neural networks using Google’s TensorFlow 1.x An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more. Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environment […]

Artificial Intelligence Tools for Cyber Attribution (SpringerBriefs in Computer Science)

Artificial Intelligence Tools for Cyber Attribution (SpringerBriefs in Computer Science)

This SpringerBrief discusses how to develop intelligent systems for cyber attribution regarding cyber-attacks. Specifically, the authors review the multiple facets of the cyber attribution problem that make it difficult for “out-of-the-box” artificial intelligence and machine learning techniques to handle.  Attributing a cyber-operation through the use of multiple pieces of technical evidence (i.e., malware reverse-engineering and source tracking) and conventional intelligence […]

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