LEADER 02356nam 2200505 450 001 9910702011203321 005 20200609125007.0 035 $a(CKB)5470000002424020 035 $a(OCoLC)1157286157 035 $a(EXLCZ)995470000002424020 100 $a20200609d2012 ua 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEffects of brush management on the hydrologic budget and water quality in and adjacent to Honey Creek State Natural Area, Comal County, Texas, 2001-10 /$fJ. Ryan Banta and Richard N. Slattery 210 1$a[Reston, Va.] :$cU.S. Department of the Interior, U.S. Geological Survey,$d2012. 215 $a1 online resource (4 unnumbered pages) $ccolor illustrations, one color map 225 1 $aFact sheet ;$v2012-3097 300 $a"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, the Edwards Region Grazing Lands Conservation Initiative, the Texas State Soil and Water Conservation Board, the San Antonio River Authority, the Edwards Aquifer Authority, Texas Parks and Wildlife, the Guadalupe Blanco River Authority, and the San Antonio Water System." 300 $a"August 2012." 320 $aIncludes bibliographical references (page 4). 606 $aBrush$xControl$zTexas$zComal County 606 $aWater quality$zTexas$zComal County 606 $aHydrology$zTexas$zComal County 615 0$aBrush$xControl 615 0$aWater quality 615 0$aHydrology 700 $aBanta$b J. Ryan$g(John Ryan),$01386302 702 $aSlattery$b Richard N. 712 02$aGeological Survey (U.S.), 712 02$aUnited States.$bNatural Resources Conservation Service. 712 02$aTexas State Soil Conservation Board. 712 02$aSan Antonio River Authority. 712 02$aEdwards Aquifer Authority (Tex.) 712 02$aTexas.$bParks and Wildlife Department. 712 02$aGuadalupe-Blanco River Authority (Tex.) 712 02$aSan Antonio Water System (Tex.) 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910702011203321 996 $aEffects of brush management on the hydrologic budget and water quality in and adjacent to Honey Creek State Natural Area, Comal County, Texas, 2001-10$93548082 997 $aUNINA LEADER 01424nam0 22003251i 450 001 UON00386766 005 20231205104553.940 010 $a978-08-13-92866-1 100 $a20101213d2009 |0itac50 ba 101 $aeng 102 $aUS 105 $a|||| ||||| 200 1 $aExhibiting slavery$ethe caribbean postmodern novel as museum$fVivian Nun Halloran 210 $aCharlottesville$aLondon$cUniversity of Virginia Press$d2009 215 $aX, 207 p.$d24 cm. 410 1$1001UON00256307$12001 $aNew world studies$1210 $aCharlottesville$aLondon$cUniversity Press of Virginia 606 $aCARAIBI NELLA LETTERATURA$3UONC038387$2FI 606 $aLETTERATURA CARAIBICA$xSec 20.$xStoria$3UONC063666$2FI 606 $aCARAIBI$xFiction$3UONC077129$2FI 620 $aUS$dCharlottesville$3UONL000900 620 $aGB$dLondon$3UONL003044 676 $a809.3$cStoria, descrizione, studio critico di pił di due letterature. Narrativa$v21 700 1$aHALLORAN$bVivian Nun$3UONV200584$0704694 712 $aUniversity of Virginia Press$3UONV277665$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00386766 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI AME VI c 2.73 0127 $eSI DA 3322 5 0127 $sBuono 996 $aExhibiting slavery$91353474 997 $aUNIOR LEADER 03694nam 22004455 450 001 9910861088903321 005 20250807153053.0 010 $a3-031-53282-1 024 7 $a10.1007/978-3-031-53282-5 035 $a(CKB)32027758500041 035 $a(MiAaPQ)EBC31342491 035 $a(Au-PeEL)EBL31342491 035 $a(DE-He213)978-3-031-53282-5 035 $a(EXLCZ)9932027758500041 100 $a20240514d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProbability and Statistics for Machine Learning $eA Textbook /$fby Charu C. Aggarwal 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (530 pages) 311 08$a3-031-53281-3 327 $aChapter. 1. Probability and Statistics: An Introduction -- Chapter. 2. Summarizing and Visualizing Data -- Chapter. 3. Probability Basics and Random Variables -- Chapter. 4. Probability Distributions -- Chapter. 5. Hypothesis Testing and Confidence Intervals -- Chapter. 6. Reconstructing Probability Distributions from Data -- Chapter. 7. Regression -- Chapter. 8. Classification: A Probabilistic View -- Chapter. 9. Unsupervised Learning: A Probabilistic View -- Chapter. 10. Discrete State Markov Processes -- Chapter. 11. Probabilistic Inequalities and Extreme Value Analysis -- Bibliography -- Index. 330 $aThis book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories: 1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapter 1 provides an overview of the area of probability and statistics as well as its relationship to machine learning. The fundamentals of probability and statistics are covered in Chapters 2 through 5. 2. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters. 3. Advanced topics: Chapter 10 is devoted to discrete-state Markov processes. It explores the application of probability and statistics to a temporal and sequential setting, although the applications extend to more complex settings such as graphical data. Chapter 11 covers a number of probabilistic inequalities and approximations. The style of writing promotes the learning of probability and statistics simultaneously with a probabilistic perspective on the modeling of machine learning applications. The book contains over 200 worked examples in order to elucidate key concepts. Exercises are included both within the text of the chapters and at the end of the chapters. The book is written for a broad audience, including graduate students, researchers, and practitioners. 606 $aMachine learning 606 $aMachine Learning 615 0$aMachine learning. 615 14$aMachine Learning. 676 $a006.31 700 $aAggarwal$b Charu C$0518673 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910861088903321 996 $aProbability and Statistics for Machine Learning$94163262 997 $aUNINA