000			02910cam a2200277zu 4500
001			88842675
003			FRCYB88842675
005			20251020123724.0
006			m o d
007			cr un
008			251020s2017 fr | o|||||0|0|||eng d
020			_a9781786462169
035			_aFRCYB88842675
040			_aFR-PaCSA _ben _c _erda
100	1		_aMcclure, Nick
245	0	1	_aTensorFlow Machine Learning Cookbook _c['Mcclure, Nick']
264		1	_bPackt Publishing _c2017
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aMcclure, Nick
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88842675 _qtext/html _a
520			_aExplore machine learning concepts using the latest numerical computing library — TensorFlow — with the help of this comprehensive cookbookAbout This BookYour quick guide to implementing TensorFlow in your day-to-day machine learning activitiesLearn advanced techniques that bring more accuracy and speed to machine learningUpgrade your knowledge to the second generation of machine learning with this guide on TensorFlowWho This Book Is ForThis book is ideal for data scientists who are familiar with C++ or Python and perform machine learning activities on a day-to-day basis. Intermediate and advanced machine learning implementers who need a quick guide they can easily navigate will find it useful.What You Will LearnBecome familiar with the basics of the TensorFlow machine learning libraryGet to know Linear Regression techniques with TensorFlowLearn SVMs with hands-on recipesImplement neural networks and improve predictionsApply NLP and sentiment analysis to your dataMaster CNN and RNN through practical recipesTake TensorFlow into productionIn DetailTensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You'll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google's machine learning library TensorFlow.This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP.Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.Style and approachThis book takes a recipe-based approach where every topic is explicated with the help of a real-world example.
999			_c1555160 _d1555160