English
  • استرجاع مجاني وسهل
  • أفضل العروض

Advanced Analytics With Spark : Patterns For Learning From Data At Scale Paperback English by Uri Laserson - 6 July 2017

الآن:
197.00 د.إ.‏شامل ضريبة القيمة المضافة
noon-marketplace
احصل عليه خلال 11 يناير
اطلب في غضون 5 ساعة 42 دقيقة
VIP ENBD Credit Card

VIP card

احصل على 5% رصيد مسترجع باستخدام بطاقة بنك المشرق نون الائتمانية. اشترك الآن. قدّم الحين

ادفع على 4 دفعات بدون فوائد بقيمة ٤٩٫٢٥ د.إ.اعرف المزيد
قسمها على 4 دفعات ب ٤٩٫٢٥ د.إ. بدون فوائد أو رسوم تأخير.اعرف المزيد
التوصيل 
بواسطة نوون
التوصيل بواسطة نوون
البائع ذو
 تقييم عالي
البائع ذو تقييم عالي
الدفع 
عند الاستلام
الدفع عند الاستلام
عملية 
تحويل آمنة
عملية تحويل آمنة
1
1 تمت الإضافة لعربة التسوق
أضف للعربة
Noon Locker
توصيل مجاني لنقطة نون ومراكز الاستلام
معرفة المزيد
free_returns
إرجاع سهل لكل المنتجات في هذا العرض.
المنتج كما في الوصف
المنتج كما في الوصف
70%
شريك لنون منذ

شريك لنون منذ

7+ سنين
نظرة عامة
المواصفات
الناشرO'Reilly Media, Inc, USA
رقم الكتاب المعياري الدولي 139781491972953
رقم الكتاب المعياري الدولي 101491972955
اللغةالإنجليزية
العنوان الفرعي للكتابPatterns For Learning From Data At Scale
وصف الكتابIn the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming. You'll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques-including classification, clustering, collaborative filtering, and anomaly detection-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 the book's patterns useful for working on your own data applications. With this book, you will: Familiarize yourself with the Spark programming model Become comfortable within the Spark ecosystem Learn general approaches in data science Examine complete implementations that analyze large public data sets Discover which machine learning tools make sense for particular problems Acquire code that can be adapted to many uses
عن المؤلفJuliet Hougland is the Head of Data Science, Engineering at Cloudera. Juliet holds an MS in Applied Mathematics from University of Colorado, Boulder and graduated Phi Beta Kappa from Reed College with a BA in Math-Physics. Uri Laserson is an Assistant Professor of Genetics at the Icahn School of Medicine at Mount Sinai, where he develops scalable technology for genomics and immunology using the Hadoop ecosystem. Sean Owen is Director of Data Science at Cloudera. He is an ApacheSpark committer and PMC member, and was an Apache Mahout committer. Sandy Ryza is a data science lead at Clover Health. Prior, he was a senior data scientist at Cloudera. He is an Apache Spark committer, Apache Hadoop PMC member, and founder of the Time Series for Spark project. He holds the Brown University computer science department's 2012 Twining award for "Most Chill." Josh Wills is the Head of Data Engineering at Slack, the founder of the Apache Crunch project, and wrote a tweet about data scientists once.
رقم الطبعة2
تاريخ النشر6 July 2017
عدد الصفحات280

Advanced Analytics With Spark : Patterns For Learning From Data At Scale Paperback English by Uri Laserson - 6 July 2017

تمت الإضافة لعربة التسوقatc
مجموع السلة 197.00 د.إ.‏
Loading