LEADER 01397nam0 22003131i 450 001 UON00023800 005 20231205102031.246 010 $a03-12-08442-0 100 $a20020107d1994 |0itac50 ba 101 $aeng 102 $aUS 105 $a|||| 1|||| 200 1 $aIndia, Pakistan and the Kashmir Dispute$eOn regional conflict and its resolution$fRobert G. Wirsing 210 $aNew York$cSt. Martin's Press$d1994 215 $aXII,337 p.$d21 cm 606 $aJAMMU (INDIA)$xSTORIA$xSEC. XX$3UONC009064$2FI 606 $aRELAZIONI INTERNAZIONALI$xINDIA/PAKISTAN$3UONC009065$2FI 606 $aKASHMIR$xSTORIA$xSEC. XX$xMOVIMENTI INDIPENDENTISTI$3UONC011112$2FI 620 $aUS$dNew York$3UONL000050 686 $aSI IV C BHA$cSUBCONT. INDIANO - STORIA CONTEMPORANEA - INDIA INDIPENDENTE$2A 700 1$aWIRSING$bRobert G.$3UONV018571$0642678 712 $aSt. Martin's Press$3UONV257118$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00023800 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI SI IV C BHA 102 N $eSI SA 84882 5 102 N 966 $aRELAZIONI INTERNAZIONALI - PAKISTAN/INDIA$zRELAZIONI INTERNAZIONALI - INDIA/PAKISTAN$3UONC009066 996 $aIndia, Pakistan and the Kashmir Dispute$91199034 997 $aUNIOR LEADER 05228nam 22006495 450 001 9910631100303321 005 20251009103122.0 010 $a9783031078651 010 $a3031078659 024 7 $a10.1007/978-3-031-07865-1 035 $a(MiAaPQ)EBC7141200 035 $a(Au-PeEL)EBL7141200 035 $a(CKB)25361047400041 035 $a(OCoLC)1351201726 035 $a(PPN)266354343 035 $a(DE-He213)978-3-031-07865-1 035 $a(EXLCZ)9925361047400041 100 $a20221115d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe Beginner's Guide to Data Science /$fby Robert Ball, Brian Rague 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (251 pages) 225 1 $aMathematics and Statistics Series 311 08$a9783031078644 311 08$a3031078640 320 $aIncludes bibliographical references and index. 327 $aChapter. 1. Introduction to Data Science -- Chapter. 2. Data Collection -- Chapter. 3. Data Wrangling -- Chapter. 4. Crash Course on Descriptive Statistics -- Chapter. 5. Inferential Statistics -- Chapter. 6. Metrics -- Chapter. 7. Recommendation Engines -- Chapter. 8. Machine Learning -- Chapter. 9 -- Natural Language Processing (NLP) -- Chapter. 10. Time Series -- Chapter. 11. Final Product. 330 $aThis book discusses the principles and practical applications of data science, addressing key topics including data wrangling, statistics, machine learning, data visualization, natural language processing and time series analysis. Detailed investigations of techniques used in the implementation of recommendation engines and the proper selection of metrics for distance-based analysis are also covered. Utilizing numerous comprehensive code examples, figures, and tables to help clarify and illuminate essential data science topics, the authors provide an extensive treatment and analysis of real-world questions, focusing especially on the task of determining and assessing answers to these questions as expeditiously and precisely as possible. This book addresses the challenges related to uncovering the actionable insights in ?big data,? leveraging database and data collection tools such as web scraping and text identification. This book is organized as 11 chapters, structuredas independent treatments of the following crucial data science topics: Data gathering and acquisition techniques including data creation Managing, transforming, and organizing data to ultimately package the information into an accessible format ready for analysis Fundamentals of descriptive statistics intended to summarize and aggregate data into a few concise but meaningful measurements Inferential statistics that allow us to infer (or generalize) trends about the larger population based only on the sample portion collected and recorded Metrics that measure some quantity such as distance, similarity, or error and which are especially useful when comparing one or more data observations Recommendation engines representing a set of algorithms designed to predict (or recommend) a particular product, service, or other item of interest a user or customer wishes to buy or utilize in some manner Machine learning implementations and associated algorithms, comprising core data science technologies with many practical applications, especially predictive analytics Natural Language Processing, which expedites the parsing and comprehension of written and spoken language in an effective and accurate manner Time series analysis, techniques to examine and generate forecasts about the progress and evolution of data over time Data science provides the methodology and tools to accurately interpret an increasing volume of incoming information in order to discern patterns, evaluate trends, and make the right decisions. The results of data science analysis provide real world answers to real world questions. Professionals working on data science and business intelligence projects as well as advanced-level students and researchers focused on data science, computer science, business and mathematics programs will benefit from this book. 410 0$aMathematics and Statistics Series 606 $aData mining 606 $aMachine learning 606 $aStatistics 606 $aData Mining and Knowledge Discovery 606 $aMachine Learning 606 $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences 615 0$aData mining. 615 0$aMachine learning. 615 0$aStatistics. 615 14$aData Mining and Knowledge Discovery. 615 24$aMachine Learning. 615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 676 $a005.7 676 $a006.312 700 $aBall$b Robert$031064 702 $aRague$b Brian 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910631100303321 996 $aThe beginner's guide to data science$93083053 997 $aUNINA