Data Science
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# Article Title
1 Agile Data Science
2 Agile Data Science 2.0
3 Apache Cassandra Essentials
4 Apache Flume 2nd Ed
5 Apache Hive Essentials
6 Bayesian Methods for Hackers
7 Becoming A Data Head
8 Beyond Big Data
9 Big Data
10 Big Data
11 Big Data Analytics
12 Big Data Analytics With Microsoft HDInsight In 24 Hours
13 Big Data Analytics with Spark
14 Big Data and the Internet of Things
15 Big Data For Chimps
16 Big Data Fundamentals
17 Big Data Made Easy
18 Big Data: A Very Short Introduction
19 D3.js in Action
20 Data Analytics With Hadoop
21 Data Analytics With Spark Using Python
22 Data Cleaning Pocket Primer
23 Data Mining, Practical Machine Learning Tools and Techniques
24 Data Professionals At Work
25 Data Science and Big Data Analytics
26 Data Science Tools
27 Data Structures The Fun Way
28 Data Visualization with Python and JavaScript
29 Doing Data Science
30 Efficient R Programming
31 Elasticsearch The Definitive Guide
32 Fast Data Processing with Spark (2nd Ed)
33 Field Guide to Hadoop
34 Getting Started With Data Science
35 Getting Started with Impala
36 Graph Analysis and Visualization
37 Hadoop Application Architectures
38 Hadoop Essentials
39 Hadoop for Finance Essentials
40 Hadoop in 24 Hours
41 Hadoop Interview Guide
42 Hadoop: The Definitive Guide (4th ed)
43 Kafka: The Definitive Guide
44 Learning Spark
45 Learning To Love Data Science
46 Mastering Apache Spark
47 Mastering Azure Analytics
48 Mastering Search Analytics
49 Monitoring Hadoop
50 Pandas for Everyone: Python Data Analysis
51 Practical Statistics for Data Scientists
52 Professional Hadoop
53 Programming Elastic MapReduce
54 Programming Skills for Data Science
55 Python for Data Science
56 QlikView Essentials
57 R for Data Analysis (In Easy Steps)
58 R for Data Analysis (In Easy Steps) 2nd Ed
59 R For Everyone, 2nd Ed
60 R in Action, 3rd Ed (Manning)
61 R in Action: Data Analysis and Graphics with R (2e)
62 Scalable Big Data Architecture
63 Spark In Action
64 Spark in Action, 2nd Ed (Manning)
65 SQL Server 2017 Machine Learning Services with R
66 Statistics Done Wrong
67 Storm Applied
68 Think Like a Data Scientist
69 Total Information Risk Management
70 Visualizing Graph Data