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Machine Learning : Theory and Applications - C.R. Rao

Machine Learning

Theory and Applications

By: C.R. Rao, Venu Govindaraju

eText | 16 May 2013

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Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.

The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security.



  • very relevant to current research challenges faced in various fields
  • self-contained reference to machine learning

  • emphasis on applications-oriented techniques

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Non-FictionMathematicsApplied MathematicsProbability & StatisticsEngineering & TechnologyMechanical Engineering & MaterialsMaterials ScienceComputing & I.T.Computer ScienceArtificial IntelligenceExpert Systems & Knowledge-Based SystemsBusiness Applications
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