LEADER 02305oam 2200565 450 001 9910824899803321 005 20210226231817.0 010 $a1-000-79221-8 010 $a1-00-333722-8 010 $a1-003-33722-8 010 $a1-000-79553-5 010 $a1-5231-3892-0 010 $a87-7022-095-6 035 $a(OCoLC)1163958139$z(OCoLC)1163532891 035 $a(CKB)4100000011341003 035 $a(MiAaPQ)EBC6241954 035 $a(MiAaPQ)EBC30251860 035 $a(Au-PeEL)EBL30251860 035 $a(EXLCZ)994100000011341003 100 $a20201020d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied data analytics $eprinciples and applications /$fJohnson I. Agbinya 205 $a1st ed. 210 1$aGistrup, Denmark :$cRiver Publishers,$d[2020] 210 4$dİ2020 215 $a1 online resource (370 pages) 225 1 $aRiver Publishers Series in Signal, Image and Speech Processing 311 08$aPrint version: 8770220964 9788770220965 (OCoLC)1097678160 320 $aIncludes bibliographical references and index. 330 $aThis text provides some of the most sought after techniques in big data analytics. Establishing strong foundations in these topics provides practical ease when big data analyses are undertaken using the widely available open source and commercially orientated computation platforms, languages and visualization systems. The book, when combined with such platforms, provides a complete set of tools required to handle big data and can lead to fast implementations and applications. The book contains a mixture of machine learning foundations, deep learning, artificial intelligence, statistics and evo. 410 0$aRiver Publishers series in signal, image and speech processing. 606 $aBig data 606 $aData mining 606 $aQuantitative research 615 0$aBig data. 615 0$aData mining. 615 0$aQuantitative research. 676 $a005.7 700 $aAgbinya$b Johnson I.$01649673 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910824899803321 996 $aApplied data analytics$94097110 997 $aUNINA