Contingent Computation offers a new theoretical perspective through which we can engage philosophically with computing. The book proves that aesthetics is a viable mode of investigating contemporary computational systems.
Key Features:• Build neural networks that can see and understand images• Build an A.I. that will learn to defeat you in a classic Atari game• Hands-on Learning Written for readers... Læs mere
Key Features: · Example-rich guide · Step-by-step guide · Move from single-machine to massive cluster Readers should have intermediate skills in Java or Scala. No previous machine learning experience is required.
Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry.
Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data.
Herbert Simon's classic work on artificial intelligence in the expanded and updated third edition from 1996, with a new introduction by John E. Laird.
In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too... Læs mere
This book gives a solid basis for conducting performance evaluations of learning algorithms in practical settings with an emphasis on... Læs mere
Machine Learning brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and... Læs mere