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No, 2016, Shroff/O'Reilly, First, India, Paperback, New, Ellen Friedman
There's growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensors, and many others. But analyzing data streams at scale has been difficult to do wellÑuntil now. This practical book delivers a deep introduction to Apache Flink, a highly innovative open source stream processor with a surprising range of capabilities.

Authors Ellen Friedman and Kostas Tzoumas show technical and nontechnical readers alike how Flink is engineered to overcome significant tradeoffs that have limited the effectiveness of other approaches to stream processing. You'll also learn how Flink has the ability to handle both stream and batch data processing with one technology.

  • Learn the consequences of not doing streaming wellÑin retail and marketing, IoT, telecom, and banking and finance
  • Explore how to design data architecture to gain the best advantage from stream processing
  • Get an overview of Flink's capabilities and features, along with examples of how companies use Flink, including in production
  • Take a technical dive into Flink, and learn how it handles time and stateful computation
  • Examine how Flink processes both streaming (unbounded) and batch (bounded) data without sacrificing performance
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Rs.275.00
No, 2016, Shroff/O'Reilly, First, India, Paperback, New, Downey

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds.

Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material.

You’ll explore:

  • Periodic signals and their spectrums
  • Harmonic structure of simple waveforms
  • Chirps and other sounds whose spectrum changes over time
  • Noise signals and natural sources of noise
  • The autocorrelation function for estimating pitch
  • The discrete cosine transform (DCT) for compression
  • The Fast Fourier Transform for spectral analysis
  • Relating operations in time to filters in the frequency domain
  • Linear time-invariant (LTI) system theory
  • Amplitude modulation (AM) used in radio

Other books in this series include Think Stats and Think Bayes, also by Allen Downey

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Rs.325.00
No, 2016, Shroff/O'Reilly, First, India, Paperback, New, Reitz

The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversity—and possibly dilution.

This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhiker’s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

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Rs.625.00
No, 2016, Shroff/O'Reilly, First, India, Paperback, New, Dale

Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations.

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Rs.900.00
No, 2016, Shroff/O'Reilly, First, India, Paperback, New, Bengfort

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce.

Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data.

  • Understand core concepts behind Hadoop and cluster computing
  • Use design patterns and parallel analytical algorithms to create distributed data analysis jobs
  • Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase
  • Use Sqoop and Apache Flume to ingest data from relational databases
  • Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames
  • Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib
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Rs.725.00
No, 2016, Shroff/O'Reilly, First, India, Paperback, New, Kazil

How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started.

Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain.

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Rs.975.00
2015, Shroff/O'Reilly, No, First, New, India, Parsian

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You’ll learn how to implement the appropriate MapReduce solution with code that you can use in your projects.

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Rs.1,550.00
2015, Shroff/O'Reilly, No, First, New, India, Bond

Despite the buzz surrounding the cloud computing, only a small percentage of organizations have actually deployed this new style of IT so far. If you're planning your long-term cloud strategy, this practical book provides insider knowledge and actionable real-world lessons regarding planning, design, operations, security, and application transformation. This book teaches business and technology managers how to transition their organization's traditional IT to cloud computing. Rather than yet another book trying to sell or convince readers on the benefits of clouds, this book provides guidance, lessons learned, and best practices on how to design, deploy, operate, and secure an enterprise cloud based on real-world experience.

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Rs.900.00
2015, Shroff/O'Reilly, No, First, New, India, Bollinger

Any good attacker will tell you that expensive security monitoring and prevention tools aren’t enough to keep you secure. This practical book demonstrates a data-centric approach to distilling complex security monitoring, incident response, and threat analysis ideas into their most basic elements. You’ll learn how to develop your own threat intelligence and incident detection strategy, rather than depend on security tools alone.

Written by members of Cisco’s Computer Security Incident Response Team, this book shows IT and information security professionals how to create an InfoSec playbook by developing strategy, technique, and architecture.

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Rs.800.00
2014, Shroff/O'Reilly, No, First, New, India, Kreibich

Application developers, take note: databases aren't just for the IS group any more. You can build database-backed applications for the desktop, Web, embedded systems, or operating systems without linking to heavy-duty client-server databases such as Oracle and MySQL. This book shows you how to use SQLite, a small and lightweight relational database engine that you can build directly into your application.

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Rs.1,250.00
2014, Shroff/O'Reilly, No, First, New, India, Lubanovic

Easy to understand and fun to read, Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned.

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Rs.1,150.00
2014, Shroff/O'Reilly, No, First, New, India, Kirk

Learn how to apply test-driven development (TDD) to machine-learning algorithms—and catch mistakes that could sink your analysis. In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you how to apply TDD to several machine-learning algorithms, including Naive Bayesian classifiers and Neural Networks.

Machine-learning algorithms often have tests baked in, but they can’t account for human errors in coding. Rather than blindly rely on machine-learning results as many researchers have, you can mitigate the risk of errors with TDD and write clean, stable machine-learning code. If you’re familiar with Ruby 2.1, you’re ready to start.


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Rs.625.00