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The Spark In The Machine

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The Spark In The Machine

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Author : Daniel Keown
language : en
Publisher: Singing Dragon
Release Date : 2014-03-20

The Spark In The Machine written by Daniel Keown and has been published by Singing Dragon this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-20 with Medical categories.

Why can salamanders grow new legs, and young children grow new finger tips, but adult humans can't regenerate? What is the electricity that flows through the human body? Is it the same thing that the Chinese call Qi? If so, what does Chinese medicine know, that western medicine ignores? Dan Keown's highly accessible, witty, and original book shows how western medicine validates the theories of Chinese medicine, and how Chinese medicine explains the mysteries of the body that western medicine largely ignores. He explains the generative force of embryology, how the hearts of two people in love (or in scientific terms `quantum entanglement') truly beat as one, how a cheating heart is also an ill heart (which is why men are twice as likely to die of a sudden heart attack with their mistress than with their wife), how neural crest cells determine our lifespan, and why Proust's madeleines evoked the memories they did. The book shows how the theories of western and Chinese medicine support each other, and how the integrated theory enlarges our understanding of how bodies work on every level. Full of good stories and surprising details, Dan Keown's book is essential reading for anyone who has ever wanted to know how the body really works.

The Spark In The Machine

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Author : Daniel Keown
language : en
Publisher: Singing Dragon
Release Date : 2014

The Imagination Machine

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Author : Martin Reeves
language : en
Publisher: Harvard Business Press
Release Date : 2021-06-08

The Imagination Machine written by Martin Reeves and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-08 with Business & Economics categories.

A guide for mining the imagination to find powerful new ways to succeed. We need imagination now more than ever—to find new opportunities, rethink our businesses, and discover paths to growth. Yet too many companies have lost their ability to imagine. What is this mysterious capacity? How does imagination work? And how can organizations keep it alive and harness it in a systematic way? The Imagination Machine answers these questions and more. Drawing on the experience and insights of CEOs across several industries, as well as lessons from neuroscience, computer science, psychology, and philosophy, Martin Reeves of Boston Consulting Group's Henderson Institute and Jack Fuller, an expert in neuroscience, provide a fascinating look into the mechanics of imagination and lay out a process for creating ideas and bringing them to life: The Seduction: How to open yourself up to surprises The Idea: How to generate new ideas The Collision: How to rethink your idea based on real-world feedback The Epidemic: How to spread an evolving idea to others The New Ordinary: How to turn your novel idea into an accepted reality The Encore: How to repeat the process—again and again. Imagination is one of the least understood but most crucial ingredients of success. It's what makes the difference between an incremental change and the kinds of pivots and paradigm shifts that are essential to transformation—especially during a crisis. The Imagination Machine is the guide you need to demystify and operationalize this powerful human capacity, to inject new life into your company, and to head into unknown territory with the right tools at your disposal.

Next Generation Machine Learning With Spark

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Author : Butch Quinto
language : en
Publisher: Apress
Release Date : 2020-02-22

Next Generation Machine Learning With Spark written by Butch Quinto and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-22 with Computers categories.

Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. What You Will Learn Be introduced to machine learning, Spark, and Spark MLlib 2.4.xAchieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM librariesDetect anomalies with the Isolation Forest algorithm for SparkUse the Spark NLP and Stanford CoreNLP libraries that support multiple languagesOptimize your ML workload with the Alluxio in-memory data accelerator for SparkUse GraphX and GraphFrames for Graph AnalysisPerform image recognition using convolutional neural networksUtilize the Keras framework and distributed deep learning libraries with Spark Who This Book Is For Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.

Spark The Definitive Guide

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Author : Bill Chambers
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-02-08

Spark The Definitive Guide written by Bill Chambers and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-08 with Computers categories.

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Sparkâ??s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples Dive into Sparkâ??s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Sparkâ??s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation

Machine Learning With Spark Second Edition

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Author : Rajdeep Dua
language : en
Publisher:
Release Date : 2016-10-31

Machine Learning With Spark Second Edition written by Rajdeep Dua and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-31 with categories.

Develop intelligent machine learning systems with SparkAbout This Book*Get to the grips with the latest version of Apache Spark*Utilize Spark's machine learning library to implement predictive analytics*Leverage Spark's powerful tools to load, analyze, clean, and transform your dataWho This Book Is ForIf you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages.What You Will Learn*Get hands-on with the latest version of Spark ML*Create your first Spark program with Scala and Python*Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2*Access public machine learning datasets and use Spark to load, process, clean, and transform data*Use Spark's machine learning library to implement programs by utilizing well-known machine learning models*Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models*Write Spark functions to evaluate the performance of your machine learning modelsIn DetailSpark ML is the machine learning module of Spark. It uses in-memory RDDs to process machine learning models faster for clustering, classification, and regression.This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML.Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML.

Machine Learning In Python

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Author : Michael Bowles
language : en
Publisher: John Wiley & Sons
Release Date : 2015-04-27

Machine Learning In Python written by Michael Bowles and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-27 with Computers categories.

Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.

Spark In Action

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Author : Petar Zecevic
language : en
Publisher: Manning
Release Date : 2016-11-26

Spark In Action written by Petar Zecevic and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-26 with Computers categories.

Summary Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Fully updated for Spark 2.0. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades. About the Book Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You'll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you'll start programming Spark using its core APIs. Along the way, you'll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book's code. What's Inside Updated for Spark 2.0 Real-life case studies Spark DevOps with Docker Examples in Scala, and online in Java and Python About the Reader Written for experienced programmers with some background in big data or machine learning. About the Authors Petar Zečević and Marko Bonaći are seasoned developers heavily involved in the Spark community. Table of Contents PART 1 - FIRST STEPS Introduction to Apache Spark Spark fundamentals Writing Spark applications The Spark API in depth PART 2 - MEET THE SPARK FAMILY Sparkling queries with Spark SQL Ingesting data with Spark Streaming Getting smart with MLlib ML: classification and clustering Connecting the dots with GraphX PART 3 - SPARK OPS Running Spark Running on a Spark standalone cluster Running on YARN and Mesos PART 4 - BRINGING IT TOGETHER Case study: real-time dashboard Deep learning on Spark with H2O

Machine Learning With Apache Spark Quick Start Guide

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Author : Jillur Quddus
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-26

Machine Learning With Apache Spark Quick Start Guide written by Jillur Quddus and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-26 with Computers categories.

Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time Key FeaturesMake a hands-on start in the fields of Big Data, Distributed Technologies and Machine LearningLearn how to design, develop and interpret the results of common Machine Learning algorithmsUncover hidden patterns in your data in order to derive real actionable insights and business valueBook Description Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data. What you will learnUnderstand how Spark fits in the context of the big data ecosystemUnderstand how to deploy and configure a local development environment using Apache SparkUnderstand how to design supervised and unsupervised learning modelsBuild models to perform NLP, deep learning, and cognitive services using Spark ML librariesDesign real-time machine learning pipelines in Apache SparkBecome familiar with advanced techniques for processing a large volume of data by applying machine learning algorithmsWho this book is for This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.

Learning Spark Sql

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Author : Aurobindo Sarkar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-07

Learning Spark Sql written by Aurobindo Sarkar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-07 with Computers categories.

Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book Learn about the design and implementation of streaming applications, machine learning pipelines, deep learning, and large-scale graph processing applications using Spark SQL APIs and Scala. Learn data exploration, data munging, and how to process structured and semi-structured data using real-world datasets and gain hands-on exposure to the issues and challenges of working with noisy and "dirty" real-world data. Understand design considerations for scalability and performance in web-scale Spark application architectures. Who This Book Is For If you are a developer, engineer, or an architect and want to learn how to use Apache Spark in a web-scale project, then this is the book for you. It is assumed that you have prior knowledge of SQL querying. A basic programming knowledge with Scala, Java, R, or Python is all you need to get started with this book. What You Will Learn Familiarize yourself with Spark SQL programming, including working with DataFrame/Dataset API and SQL Perform a series of hands-on exercises with different types of data sources, including CSV, JSON, Avro, MySQL, and MongoDB Perform data quality checks, data visualization, and basic statistical analysis tasks Perform data munging tasks on publically available datasets Learn how to use Spark SQL and Apache Kafka to build streaming applications Learn key performance-tuning tips and tricks in Spark SQL applications Learn key architectural components and patterns in large-scale Spark SQL applications In Detail In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help you understand the methods used to implement typical use-cases for various types of applications. You will get a walkthrough of the key concepts and terms that are common to streaming, machine learning, and graph applications. You will also learn key performance-tuning details including Cost Based Optimization (Spark 2.2) in Spark SQL applications. Finally, you will move on to learning how such systems are architected and deployed for a successful delivery of your project. Style and approach This book is a hands-on guide to designing, building, and deploying Spark SQL-centric production applications at scale.

The Spark In The Machine

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