MARC Record from marc_columbia

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001 13668438
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007 cr cnu---unuuu
008 170304s2017 enk ob 001 0 eng d
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035 $a(NNC)13668438
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020 $a9781786466303$q(electronic bk.)
020 $a1786466309$q(electronic bk.)
020 $z1786462168
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037 $a993223$bMIL
037 $a2C89606E-A4EC-4AF8-852E-6CA22959512C$bOverDrive, Inc.$nhttp://www.overdrive.com
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082 04 $a006.3$223
049 $aZCUA
100 1 $aMcClure, Nick.
245 10 $aTensorFlow Machine Learning Cookbook.
260 $aBirmingham :$bPackt Publishing,$c2017.
300 $a1 online resource (370 pages)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
588 0 $aPrint version record.
505 0 $aCover; Copyright; Credits; About the Author; About the Reviewer; www.PacktPub.com; Customer Feedback; Table of Contents; Preface; Chapter 1: Getting Started with TensorFlow; Introduction; How TensorFlow Works; Declaring Tensors; Using Placeholders and Variables; Working with Matrices; Declaring Operations; Implementing Activation Functions; Working with Data Sources; Additional Resources; Chapter 2: The TensorFlow Way; Introduction; Operations in a Computational Graph; Layering Nested Operations; Working with Multiple Layers; Implementing Loss Functions; Implementing Back Propagation.
505 8 $aWorking with Batch and Stochastic TrainingCombining Everything Together; Evaluating Models; Chapter 3: Linear Regression; Introduction; Using the Matrix Inverse Method; Implementing a Decomposition Method; Learning The TensorFlow Way of Linear Regression; Understanding Loss Functions in Linear Regression; Implementing Deming regression; Implementing Lasso and Ridge Regression; Implementing Elastic Net Regression; Implementing Logistic Regression; Chapter 4: Support Vector Machines; Introduction; Working with a Linear SVM; Reduction to Linear Regression; Working with Kernels in TensorFlow.
505 8 $aImplementing a Non-Linear SVMImplementing a Multi-Class SVM; Chapter 5: Nearest Neighbor Methods; Introduction; Working with Nearest Neighbors; Working with Text-Based Distances; Computing with Mixed Distance Functions; Using an Address Matching Example; Using Nearest Neighbors for Image Recognition; Chapter 6: Neural Networks; Introduction; Implementing Operational Gates; Working with Gates and Activation Functions; Implementing a One-Layer Neural Network; Implementing Different Layers; Using a Multilayer Neural Network; Improving the Predictions of Linear Models.
505 8 $aLearning to Play Tic Tac ToeChapter 7: Natural Language Processing; Introduction; Working with bag of words; Implementing TF-IDF; Working with Skip-gram Embeddings; Working with CBOW Embeddings; Making Predictions with Word2vec; Using Doc2vec for Sentiment Analysis; Chapter 8: Convolutional Neural Networks; Introduction; Implementing a Simpler CNN; Implementing an Advanced CNN; Retraining Existing CNNs models; Applying Stylenet/Neural-Style; Implementing DeepDream; Chapter 9: Recurrent Neural Networks; Introduction; Implementing RNN for Spam Prediction; Implementing an LSTM Model.
505 8 $aStacking multiple LSTM LayersCreating Sequence-to-Sequence Models; Training a Siamese Similarity Measure; Chapter 10: Taking TensorFlow to Production; Introduction; Implementing unit tests; Using Multiple Executors; Parallelizing TensorFlow; Taking TensorFlow to Production; Productionalizing TensorFlow -- An Example; Chapter 11: More with TensorFlow; Introduction; Visualizing graphs in Tensorboard; There's more ... ; Working with a Genetic Algorithm; Clustering Using K-Means; Solving a System of ODEs; Index.
504 $aIncludes bibliographical references and index.
520 $a"Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbook."--Cover.
630 00 $aTensorFlow (Electronic resource)
650 0 $aMachine learning.
650 0 $aArtificial intelligence.
650 2 $aArtificial Intelligence
650 6 $aApprentissage automatique.
650 6 $aIntelligence artificielle.
650 7 $aartificial intelligence.$2aat
650 7 $aCOMPUTERS$xGeneral.$2bisacsh
650 7 $aArtificial intelligence.$2fast$0(OCoLC)fst00817247
650 7 $aMachine learning.$2fast$0(OCoLC)fst01004795
655 4 $aElectronic books.
776 08 $iPrint version:$aMcClure, Nick.$tTensorFlow Machine Learning Cookbook.$dBirmingham : Packt Publishing, ©2017
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio13668438$zAll EBSCO eBooks
852 8 $blweb$hEBOOKS