000			01994cam a2200397Ii 4500
001			on1112158811
003			OCoLC
005			20220524082625.0
007			ta
008			200415s2019 xx a r 000 0 eng d
020			_a9781075277313
020			_a1075277310
035			_a(OCoLC)1112158811
040			_aKNJ _beng _erda _cKNJ _dOCLCF
041	0		_aeng
082	0	4	_a005.133 _bW17d 2019
100	1		_aWalker, Brian, _eautor.
245	1	0	_aDeep learning with Python : _bcomprehensive beginners guide to learn and understand the realms of deep learning with Python / _cBrian Walker.
264		1	_a[S. l. ] : _b[s. n.] , _c[2019]
264		4	_c©2019.
300			_a144 páginas : _bilustraciones ; _c23 cm.
336			_atexto _btxt _2rdacontent
337			_asin mediación _bn _2rdamedia
338			_avolúmen _bnc _2rdacarrier
504			_aIncluye bibliografía
520			_aArtificial intelligence takes many shapes and forms. At this point in its evolution, machine learning and deep learning are two of the most common shapes it takes. This is primarily because we are at a point where we have discovered how to create networks of information that can actually be filtered and processed just as a normal human cognitive process would be. Beyond all those shapes and forms of AI, though, this entire concept is built based on a few basic ideas: Information is power, Neural networks can imitate the human brain, Programmers can create machine programs that enable them to filter information in a specific way, that allows them to draw conclusions and grow their learning based on that.
650		0	_aInteligencia artifical _9331119
650		0	_aAprendizaje automático (Inteligencia artificial) _9302324
650		4	_aPython (Lenguaje de programación de computadores). _9102621
900			_aDSÑ
900			_aAYN
900			_aTC
942			_2ddc _cGEN _n0
948			_hNO HOLDINGS IN UN@ - 2 OTHER HOLDINGS
991			_aEYR _bAndrés Hernández Gutiérrez _cOT19
999			_c147930 _d147930