000			01488nam a22002057a 4500
999			_c2631 _d2631
005			20220716130745.0
008			220716b ||||| |||| 00| 0 eng d
020			_a9783030686390
082			_a006.31 _bGIA
100			_aGianfagna, Leonida _97600
245			_aExplainable AI with python
260			_bSpringer _aSwitzerland _c2021
300			_aviii, 202 p.
365			_aEURO _b59.99
520			_aThis book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others. Progress in Machine Learning is increasing the use of artificial agents to perform critical tasks previously handled by humans (healthcare, legal and finance, among others). While the principles that guide the design of these agents are understood, most of the current deep-learning models are "opaque" to human understanding. Explainable AI with Python fills the current gap in literature on this emerging topic by taking both a theoretical and a practical perspective, making the reader quickly capable of working with tools and code for Explainable AI.
650			_aMachine learning _92343
650			_aPython (Computer program language) _97601
700			_aCecco, Antonio Di _97602
942			_2ddc _cBK