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ISBN
| 9781491972953 | |
DDC
| 006.312 | |
Nhan đề
| Advanced analytics with Spark : patterns for learning from data at scale / Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills. | |
Lần xuất bản
| Second edition. | |
Thông tin xuất bản
| Beijing : O'Reilly, 2017 | |
Mô tả vật lý
| xii, 264 pages :illustrations ;24 cm | |
Tóm tắt
| The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by presenting examples and a set of self-contained patterns for performing large-scale data analysis with Spark. You'll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques-classification, collaborative filtering, and anomaly detection among others-to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you'll find these patterns useful for working on your own data applications. | |
Thuật ngữ chủ đề
| Big data. | |
Thuật ngữ chủ đề
| Data mining-Computer programs. | |
Khoa
| Khoa Công nghệ Thông tin | |
Tác giả(bs) CN
| Laserson, Uri | |
Tác giả(bs) CN
| Owen, Sean | |
Tác giả(bs) CN
| Wills, Josh | |
Tác giả(bs) CN
| Ryza, Sandy | |
Địa chỉ
| 300Q12_Kho Mượn_02(2): 067272-3 |
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000
| 02565nam a22003737# 4500 |
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| 001 | 17552 |
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| 002 | 2 |
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| 004 | D2BD3188-8D7F-45C1-A2F2-17BA16E6A632 |
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| 005 | 201909181343 |
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| 008 | 190918s2017 cc a b 001 0 eng d |
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| 009 | 1 0 |
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| 020 | |a9781491972953|c1675000 |
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| 039 | |a20190918134345|bquyennt|c20190918134055|dquyennt|y20190918133506|zquyennt |
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| 040 | |aNTT |
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| 041 | |aeng |
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| 044 | |acc |
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| 082 | |a006.312|bA2442|223 |
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| 245 | 00|aAdvanced analytics with Spark :|bpatterns for learning from data at scale /|cSandy Ryza, Uri Laserson, Sean Owen, and Josh Wills. |
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| 250 | |aSecond edition. |
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| 260 | |aBeijing : |bO'Reilly, |c2017 |
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| 300 | |axii, 264 pages :|billustrations ;|c24 cm |
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| 504 | |aIncludes bibliographical references and index. |
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| 520 | |aThe authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by presenting examples and a set of self-contained patterns for performing large-scale data analysis with Spark. You'll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques-classification, collaborative filtering, and anomaly detection among others-to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you'll find these patterns useful for working on your own data applications. |
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| 541 | |aMua |
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| 630 | 00|aSpark (Electronic resource : Apache Software Foundation) |
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| 650 | 0|aBig data. |
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| 650 | 0|aData mining|xComputer programs. |
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| 690 | |aKhoa Công nghệ Thông tin |
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| 700 | |aLaserson, Uri |
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| 700 | |aOwen, Sean |
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| 700 | |aWills, Josh |
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| 700 | 1 |aRyza, Sandy|eauthor. |
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| 852 | |a300|bQ12_Kho Mượn_02|j(2): 067272-3 |
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| 856 | 1|uhttp://elib.ntt.edu.vn/documentdata01/2 tailieuthamkhao/000 tinhocthongtin/anhbiasach/17552_advanced analytics with sparkthumbimage.jpg |
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| 890 | |a2|b0|c0|d0 |
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