Building machine learning systems with Python (779436), страница 47
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See penalizedregressionresources, machine learningblogs 292books 291competition 293data sources 293online courses 291question and answer sites 292Ridge Regression 165[ 299 ]StarClusterabout 288URL 288used, for automating clustergeneration 284-287stemming 60root mean square error (RMSE)about 159advantage 160roundness 42Ssave() function 206scale-invariant feature transform (SIFT) 219scikit-learn classificationabout 43, 44decision boundaries, examining 45-47SciKit library 52SciPyabout 6learning 12, 13toolboxes 12, 13URL 6Securities and ExchangeCommission (SEC) 168Seeds datasetabout 41features 41sentiment analysisabout 123first classifier, creating 134Naïve Bayes classifier 124roadmap, sketching 123tweets, cleaning 146Twitter data, fetching 124SentiWordNetURL 150similarity measuringabout 52bag of word approach 53SoXURL 200sparse 165sparsity 83specgram function 201Speeded Up Robust Features (SURF) 235stacked learning 186Stack OverflowURL 5TTalkbox SciKitURL 214task 265testing accuracy 36TfidfVectorizer parameter 141thresholding 222TimeToAnswer 101tiny application, machine learningabout 13data, cleaning 15, 16data, preprocessing 15, 16data, reading in 14, 15learning algorithm, selecting 17model, selecting 17, 18Title attribute 99toolboxes, SciPycluster 12constants 13fftpack 13integrate 13interpolate 13io 13linalg 13ndimage 13odr 13optimize 13signal 13sparse 13spatial 13special 13stats 13topic modeling 79topicsabout 79documents comparing by 86-89[ 300 ]number of topics, selecting 92, 93training accuracy 36train_model()function 136transform(documents) method 152tweetscleaning 146-148Twitter datafetching 124two-levels of cross-validation 171TwoToRealURL 292Uunderfitting 24Vvirtual machines, AWScreating 276-282jug, running on cloud machine 283, 284Python packages, installing on AmazonLinux 282visual words 237WWikipedia dumpURL 89word typesabout 148determining 148estimator 152implementing 155, 156ViewCount 99[ 301 ]Thank you for buyingBuilding Machine Learning Systemswith PythonSecond EditionAbout Packt PublishingPackt, pronounced 'packed', published its first book, Mastering phpMyAdmin for EffectiveMySQL Management, in April 2004, and subsequently continued to specialize in publishinghighly focused books on specific technologies and solutions.Our books and publications share the experiences of your fellow IT professionals in adaptingand customizing today's systems, applications, and frameworks.
Our solution-based booksgive you the knowledge and power to customize the software and technologies you're usingto get the job done. Packt books are more specific and less general than the IT books you haveseen in the past. Our unique business model allows us to bring you more focused information,giving you more of what you need to know, and less of what you don't.Packt is a modern yet unique publishing company that focuses on producing quality,cutting-edge books for communities of developers, administrators, and newbies alike.For more information, please visit our website at www.packtpub.com.About Packt Open SourceIn 2010, Packt launched two new brands, Packt Open Source and Packt Enterprise, in orderto continue its focus on specialization. This book is part of the Packt Open Source brand,home to books published on software built around open source licenses, and offeringinformation to anybody from advanced developers to budding web designers.
The OpenSource brand also runs Packt's Open Source Royalty Scheme, by which Packt gives a royaltyto each open source project about whose software a book is sold.Writing for PacktWe welcome all inquiries from people who are interested in authoring. Book proposals shouldbe sent to author@packtpub.com. If your book idea is still at an early stage and you wouldlike to discuss it first before writing a formal book proposal, then please contact us; one of ourcommissioning editors will get in touch with you.We're not just looking for published authors; if you have strong technical skills but no writingexperience, our experienced editors can help you develop a writing career, or simply get someadditional reward for your expertise.Mastering Machine Learning withscikit-learnISBN: 978-1-78398-836-5Paperback: 238 pagesApply effective learning algorithms to real-worldproblems using scikit-learn1.Design and troubleshoot machine learningsystems for common tasks including regression,classification, and clustering.2.Acquaint yourself with popular machinelearning algorithms, including decision trees,logistic regression, and support vector machines.3.A practical example-based guide to help yougain expertise in implementing and evaluatingmachine learning systems using scikit-learn.Scala for Machine LearningISBN: 978-1-78355-874-2Paperback: 520 pagesLeverage Scala and Machine Learning to constructand study systems that can learn from data1.Explore a broad variety of data processing,machine learning, and genetic algorithmsthrough diagrams, mathematical formulation,and source code.2.Leverage your expertise in Scala programmingto create and customize AI applications withyour own scalable machine learning algorithms.3.Experiment with different techniques,and evaluate their benefits and limitationsusing real-world financial applications, in atutorial style.Please check www.PacktPub.com for information on our titlesR Machine Learning EssentialsISBN: 978-1-78398-774-0Paperback: 218 pagesGain quick access to the machine learning conceptsand practical applications using the R developmentenvironment1.Build machine learning algorithms using themost powerful tools in R.2.Identify business problems and solve them bydeveloping effective solutions.3.Hands-on tutorial explaining the conceptsthrough lots of practical examples, tipsand tricks.Clojure for Machine LearningISBN: 978-1-78328-435-1Paperback: 292 pagesSuccessfully leverage advanced machine learningtechniques using the Clojure ecosystem1.Covers a lot of machine learning techniqueswith Clojure programming.2.Encompasses precise patterns in data topredict future outcomes using various machinelearning techniques.3.Packed with several machine learning librariesavailable in the Clojure ecosystem.Please check www.PacktPub.com for information on our titles.
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