000			nam a22 4500
999			_c7677 _d7677
005			20181117155228.0
008			181117b xxu||||| |||| 00| 0 eng d
020			_a9789352137305
040			_cAIKTC-KRRC
041			_aENG
082			_2DDC23 _a006.31 _bALB
100			_95147 _aAlbon, Chris
245			_aMachine learning with python cookbook _b: Practical soulutions from preprocessing to deep learning
250			_a1st
260			_aSebastopol _bO'Reilly Media, Inc. _c2018
300			_axiii, 349p. _bPaperback _c23*17.6 cm
520			_aThis practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications
650		0	_94622 _aComputer Engineering
653			_aData Wrangling
653			_aNumerical Data
653			_aLinear Regression
942			_2ddc _cBK