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Machine Learning Year 4 (MCSL)
(13 Books)
1
Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems
by
Peter Dayan
4.22 avg rating — 302 ratings
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2
Algorithmic Game Theory
by
Noam Nisan
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4.20 avg rating — 79 ratings
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3
Springer Handbook of Robotics
by
Bruno Siciliano
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4.47 avg rating — 36 ratings
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An Introduction to Computational Learning Theory
by
Michael J. Kearns
3.90 avg rating — 40 ratings
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5
The Handbook of Computational Linguistics and Natural Language Processing
by
Alexander Clark
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4.50 avg rating — 10 ratings
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6
Reinforcement Learning and Optimal Control
by
Dimitri P. Bertsekas
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7
Handbook of Knowledge Representation
by
Frank van Harmelen
4.25 avg rating — 4 ratings
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8
Graph Representation Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning, 46)
by
William L. Hamilton
4.42 avg rating — 36 ratings
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9
Search and Optimization by Metaheuristics: Techniques and Algorithms Inspired by Nature
by
Ke-Lin Du
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4.00 avg rating — 1 rating
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A Concise Introduction to Decentralized POMDPs
by
Frans A. Oliehoek
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Neural Networks and Statistical Learning
by
Ke-Lin Du
4.67 avg rating — 3 ratings
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12
Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science, Series Number 30)
by
M.H.G. Anthony
3.60 avg rating — 5 ratings
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Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics, Series Number 24)
by
Felipe Cucker
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