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Free Data Science, Analytics, Machine Learning and IoT Books

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Streaming Systems: The what, where, when, and how of large-scale data processing.
Hadoop Big Data Analysis Framework.
The Data Scientist's Guide to Apache Spark.
BI & Analytics on a Data Lake.
A Gentle Introduction to Apache Spark. Learn why Spark is a popular choice for data analytics, what tools and features are available, its basic architecture and how to get started right away through interactive sample code
The Elements of Data Analytic Style. This book is focused on the details of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks
The Data Analytics Handbook. Interviews with data scientists, data analysts, CEOs, managers, and researchers at the cutting edge of the data science industry
O'Reilly Free Data Ebooks. The best data insights from O'Reilly editors, authors, and Strata speakers for you in one place
Implementing Big Data Analysis. Learn how to use Windows Azure HDInsight to process big data and to generate results for analysis and reporting with Microsoft data tools
Working with big data on Azure. Explores the impact of big data on businesses, and shows how to deploy Hadoop clusters and run MapReduce on Azure to turn this data into insights
Frontiers in Massive Data Analysis. The promise and perils of massive data
The Free Hive Book. A free electronic book about Apache Hive. The book is geared towards SQL-knowledgeable business users with some advanced tips for devops
Big Data Sourcebook: Your Guide to the Data Revolution. Guide to the enterprise and technology issues of the 'big data' phenomenon
No More Secrets with Big Data Analytics. A sound basis for updating or refining your understanding of Big Data Analytics
Harnessing The Power Of Big Data Through Education And Data-Driven Decision Making.
Planning for Big Data. A CIO's Handbook to the Changing Data Landscape
School of Data. Teaching people how to gain powerful insights and create compelling stories using data
SQL School by Mode Analytics. Made up of 2 modules: a) SQL skill building b) Analytics training - learning to think like an analyst
The Promise and Peril of Big Data. New challenges and questions facing big data: from ethics to scientific methodologies to evolution of knowledge
Disruptive Possibilities: How Big Data Changes Everything. Evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds
Advanced Data Analysis from an Elementary Point of View. Modern methods of data analysis and the considerations which go into choosing the right method for the job at hand
Big Data Analytics Infrastructure for Dummies. The emphasis is on hardware infrastructure - processing, storage, systems software, and internal networks
Data Science and Cognitive Computing Courses. Build Data Science and Cognitive Computing skills for free today
Big Data Now: Current Perspective from O'Reilly Media. Top big data posts from late fall 2012 through late fall 2013
Business Analytics in Retail for Dummies. Using business analytics to discover insights that, when acted on, drive revenue growth and improve customer relations
Fundamental Numerical Methods and Data Analysis. A wide range of courses that discuss numerical methods used in science
Data Blending for Dummies. Simplifying data blending for the analyst
Field Guide to Hadoop. An introduction to Hadoop, its ecosystem and aligned technologies
Big Data Analytics with Twitter. Taught in close collaboration with Twitter, focuses on the tools and algorithms for data analysis as applied to Twitter's data
Real-Time Big Data Analytics: Emerging Architecture. Using real-time big data analytics (RTBDA) to improve sales, lower costs a ticket to improved sales, higher profits and lower marketing costs
Time Series Databases: New Ways to Store and Access Data. A new world of time series data calls for new approaches and new tools to store and access it
Modeling with Data: Tools and Techniques for Scientific Computing. Executing computationally intensive analyses on very large data sets
The Fourth Paradigm: Data-Intensive Scientific Discovery. This book is about a new, fourth paradigm for science based on data-intensive computing

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