| 000 | 01609nam a2200337 i 4500 | ||
|---|---|---|---|
| 001 | 991001134073707456 | ||
| 005 | 20250612075549.0 | ||
| 008 | 150407s2015 flua b 001 0 eng | ||
| 010 |
_a 2014434325 _z 2015302878 |
||
| 020 | _a9781466583283 | ||
| 020 | _a1466583282 | ||
| 035 | _a(DLC) 2014434325 | ||
| 040 |
_aDLC _beng _erda _cDLC |
||
| 042 | _apcc | ||
| 050 | 0 | 0 |
_aQ325.5 _b.M368 2015 |
| 100 | 1 | _aMarsland, Stephen. | |
| 245 | 1 | 0 |
_aMachine learning : _ban algorithmic perspective / _cStephen Marsland. |
| 250 | _aSecond edition. | ||
| 264 | 1 |
_aBoca Raton : _bCRC Press, _c[2015] |
|
| 300 |
_axx, 437 pages : _billustrations ; _c25 cm. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_aunmediated _bn _2rdamedia |
||
| 338 |
_avolume _bnc _2rdacarrier |
||
| 490 | 0 | _aChapman & Hall/CRC machine learning & pattern recognition series | |
| 500 | _a"A Chapman & Hall book." | ||
| 504 | _aIncludes bibliographical references and index. | ||
| 505 | 0 | _aIntroduction -- Preliminaries -- Neurons, neural networks, and linear discriminants -- The multi-layer perceptron -- Radial basis functions and splines -- Dimensionality reduction -- Probabilistic learning -- Support vector machines -- Optimisation and search -- Evolutionary learning -- Reinforcement learning -- Learning with trees -- Decision by committee: ensemble learning -- Unsupervised learning -- Markov chain Monte Carlo (MCMC) methods -- Graphical models -- Symmetric weights and deep belief networks -- Gaussian processes -- Python. | |
| 650 | 0 | _aMachine learning. | |
| 650 | 0 | _aAlgorithms. | |
| 960 |
_aPOL-2256 _b2440142 _c1 |
||
| 999 |
_c7009 _d7009 |
||