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008			171207s2018 xxu|||| o |||| 0|eng
010			_a 2019765102
020			_a9781484232859
024	7		_a10.1007/978-1-4842-3285-9 _2doi
035			_a(DE-He213)978-1-4842-3285-9
040			_aDLC _beng _epn _erda _cDLC
072		7	_aCOM004000 _2bisacsh
072		7	_aUYQ _2bicssc
072		7	_aUYQ _2thema
082	0	4	_a006.3 _21 _bNANA
100	1		_aNandy, Abhishek, _931868
245	1	0	_aReinforcement learning : _bwith open AI, tensorflow and keras using python / _cBy Abhishek Nandy andManisha Biswas.
250			_a1st ed.
260			_aNew York : _bApress , _c2019.
264		1	_aBerkeley, CA : _bApress : _bImprint: Apress, _c2018.
300			_axiii, 167p. ; _c23 cm.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aChapter 1: Reinforcement Learning basics -- Chapter 2: Theory and Algorithms -- Chapter 3: Open AI basics -- Chapter 4: Getting to know Open AI and Open AI Gym the developers way -- Chapter 5: Reinforcement learning using Tensor Flow environment and Keras -- Chapter 6 Google's DeepMind and the future of Reinforcement Learning.
520			_aMaster reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You'll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov's Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before looking at Open AI Gym. You'll then learn about Swarm Intelligence with Python in terms of reinforcement learning. The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There's also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google's Deep Mind and see scenarios where reinforcement learning can be used. You will: Absorb the core concepts of the reinforcement learning process Use advanced topics of deep learning and AI Work with Open AI Gym, Open AI, and Python Harness reinforcement learning with TensorFlow and Keras using Python.
588			_aDescription based on publisher-supplied MARC data.
650		0	_aReinforcement learning basics _931869
650		0	_aOpenAI basics _931870
650	1	4	_aApplying python to reinforcement learning _0https://scigraph.springernature.com/ontologies/product-market-codes/I21000 _931871
650	2	4	_aPython. _0https://scigraph.springernature.com/ontologies/product-market-codes/I29080 _931872
700	1		_aBiswas, Manisha. _931873
776	0	8	_iPrint version: _tReinforcement learning _z9781484232842 _w(DLC) 2017962867
776	0	8	_iPrinted edition: _z9781484232842
776	0	8	_iPrinted edition: _z9781484232866
776	0	8	_iPrinted edition: _z9781484247358
906			_a0 _bibc _corigres _du _encip _f20 _gy-gencatlg
942			_2ddc _cBK _e1st _k006.3 NANA
999			_c222627 _d222627