Mahout In Action

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Mahout in Action

Author : Sean Owen
Publisher : Simon and Schuster
ISBN 13 : 1638355371
Total Pages : 616 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Mahout in Action by : Sean Owen

Download or read book Mahout in Action written by Sean Owen and published by Simon and Schuster. This book was released on 2011-10-04 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Mahout in Action is a hands-on introduction to machine learning with Apache Mahout. Following real-world examples, the book presents practical use cases and then illustrates how Mahout can be applied to solve them. Includes a free audio- and video-enhanced ebook. About the Technology A computer system that learns and adapts as it collects data can be really powerful. Mahout, Apache's open source machine learning project, captures the core algorithms of recommendation systems, classification, and clustering in ready-to-use, scalable libraries. With Mahout, you can immediately apply to your own projects the machine learning techniques that drive Amazon, Netflix, and others. About this Book This book covers machine learning using Apache Mahout. Based on experience with real-world applications, it introduces practical use cases and illustrates how Mahout can be applied to solve them. It places particular focus on issues of scalability and how to apply these techniques against large data sets using the Apache Hadoop framework. This book is written for developers familiar with Java -- no prior experience with Mahout is assumed. Owners of a Manning pBook purchased anywhere in the world can download a free eBook from manning.com at any time. They can do so multiple times and in any or all formats available (PDF, ePub or Kindle). To do so, customers must register their printed copy on Manning's site by creating a user account and then following instructions printed on the pBook registration insert at the front of the book. What's Inside Use group data to make individual recommendations Find logical clusters within your data Filter and refine with on-the-fly classification Free audio and video extras Table of Contents Meet Apache Mahout PART 1 RECOMMENDATIONS Introducing recommenders Representing recommender data Making recommendations Taking recommenders to production Distributing recommendation computations PART 2 CLUSTERING Introduction to clustering Representing data Clustering algorithms in Mahout Evaluating and improving clustering quality Taking clustering to production Real-world applications of clustering PART 3 CLASSIFICATION Introduction to classification Training a classifier Evaluating and tuning a classifier Deploying a classifier Case study: Shop It To Me

Solr in Action

Author : Timothy Potter
Publisher : Simon and Schuster
ISBN 13 : 1638351236
Total Pages : 939 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Solr in Action by : Timothy Potter

Download or read book Solr in Action written by Timothy Potter and published by Simon and Schuster. This book was released on 2014-03-25 with total page 939 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Solr in Action is a comprehensive guide to implementing scalable search using Apache Solr. This clearly written book walks you through well-documented examples ranging from basic keyword searching to scaling a system for billions of documents and queries. It will give you a deep understanding of how to implement core Solr capabilities. About the Book Whether you're handling big (or small) data, managing documents, or building a website, it is important to be able to quickly search through your content and discover meaning in it. Apache Solr is your tool: a ready-to-deploy, Lucene-based, open source, full-text search engine. Solr can scale across many servers to enable real-time queries and data analytics across billions of documents. Solr in Action teaches you to implement scalable search using Apache Solr. This easy-to-read guide balances conceptual discussions with practical examples to show you how to implement all of Solr's core capabilities. You'll master topics like text analysis, faceted search, hit highlighting, result grouping, query suggestions, multilingual search, advanced geospatial and data operations, and relevancy tuning. This book assumes basic knowledge of Java and standard database technology. No prior knowledge of Solr or Lucene is required. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. What's Inside How to scale Solr for big data Rich real-world examples Solr as a NoSQL data store Advanced multilingual, data, and relevancy tricks Coverage of versions through Solr 4.7 About the Authors Trey Grainger is a director of engineering at CareerBuilder. Timothy Potter is a senior member of the engineering team at LucidWorks. The authors work on the scalability and reliability of Solr, as well as on recommendation engine and big data analytics technologies. Table of Contents PART 1 MEET SOLR Introduction to Solr Getting to know Solr Key Solr concepts Configuring Solr Indexing Text analysis PART 2 CORE SOLR CAPABILITIES Performing queries and handling results Faceted search Hit highlighting Query suggestions Result grouping/field collapsing Taking Solr to production PART 3 TAKING SOLR TO THE NEXT LEVEL SolrCloud Multilingual search Complex query operations Mastering relevancy

Lucene in Action

Author : Otis Gospodnetic
Publisher : Simon and Schuster
ISBN 13 : 1638354731
Total Pages : 742 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Lucene in Action by : Otis Gospodnetic

Download or read book Lucene in Action written by Otis Gospodnetic and published by Simon and Schuster. This book was released on 2010-07-08 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: When Lucene first hit the scene five years ago, it was nothing short ofamazing. By using this open-source, highly scalable, super-fast search engine,developers could integrate search into applications quickly and efficiently.A lot has changed since then-search has grown from a "nice-to-have" featureinto an indispensable part of most enterprise applications. Lucene now powerssearch in diverse companies including Akamai, Netflix, LinkedIn,Technorati, HotJobs, Epiphany, FedEx, Mayo Clinic, MIT, New ScientistMagazine, and many others. Some things remain the same, though. Lucene still delivers high-performancesearch features in a disarmingly easy-to-use API. Due to its vibrant and diverseopen-source community of developers and users, Lucene is relentlessly improving,with evolutions to APIs, significant new features such as payloads, and ahuge increase (as much as 8x) in indexing speed with Lucene 2.3. And with clear writing, reusable examples, and unmatched advice on bestpractices, Lucene in Action, Second Edition is still the definitive guide todeveloping with Lucene. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

Tika in Action

Author : Jukka L. Zitting
Publisher : Simon and Schuster
ISBN 13 : 1638352631
Total Pages : 365 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Tika in Action by : Jukka L. Zitting

Download or read book Tika in Action written by Jukka L. Zitting and published by Simon and Schuster. This book was released on 2011-11-30 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Tika in Action is a hands-on guide to content mining with Apache Tika. The book's many examples and case studies offer real-world experience from domains ranging from search engines to digital asset management and scientific data processing. About the Technology Tika is an Apache toolkit that has built into it everything you and your app need to know about file formats. Using Tika, your applications can discover and extract content from digital documents in almost any format, including exotic ones. About this Book Tika in Action is the ultimate guide to content mining using Apache Tika. You'll learn how to pull usable information from otherwise inaccessible sources, including internet media and file archives. This example-rich book teaches you to build and extend applications based on real-world experience with search engines, digital asset management, and scientific data processing. In addition to architectural overviews, you'll find detailed chapters on features like metadata extraction, automatic language detection, and custom parser development. This book is written for developers who are new to both Scala and Lift and covers just enough Scala to get you started. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside Crack MS Word, PDF, HTML, and ZIP Integrate with search engines, CMS, and other data sources Learn through experimentation Many examples This book requires no previous knowledge of Tika or text mining techniques. It assumes a working knowledge of Java. ========================================== Table of Contents PART 1 GETTING STARTED The case for the digital Babel fish Getting started with Tika The information landscape PART 2 TIKA IN DETAIL Document type detection Content extraction Understanding metadata Language detection What's in a file? PART 3 INTEGRATION AND ADVANCED USE The big picture Tika and the Lucene search stack Extending Tika PART 4 CASE STUDIES Powering NASA science data systems Content management with Apache Jackrabbit Curating cancer research data with Tika The classic search engine example

Machine Learning and Big Data

Author : Uma N. Dulhare
Publisher : John Wiley & Sons
ISBN 13 : 1119654742
Total Pages : 544 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis Machine Learning and Big Data by : Uma N. Dulhare

Download or read book Machine Learning and Big Data written by Uma N. Dulhare and published by John Wiley & Sons. This book was released on 2020-09-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.

Taming Text

Author : Grant Ingersoll
Publisher : Simon and Schuster
ISBN 13 : 1638353867
Total Pages : 467 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Taming Text by : Grant Ingersoll

Download or read book Taming Text written by Grant Ingersoll and published by Simon and Schuster. This book was released on 2012-12-20 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Taming Text, winner of the 2013 Jolt Awards for Productivity, is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. This book explores how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. The book guides you through examples illustrating each of these topics, as well as the foundations upon which they are built. About this Book There is so much text in our lives, we are practically drowningin it. Fortunately, there are innovative tools and techniquesfor managing unstructured information that can throw thesmart developer a much-needed lifeline. You'll find them in thisbook. Taming Text is a practical, example-driven guide to working withtext in real applications. This book introduces you to useful techniques like full-text search, proper name recognition,clustering, tagging, information extraction, and summarization.You'll explore real use cases as you systematically absorb thefoundations upon which they are built.Written in a clear and concise style, this book avoids jargon, explainingthe subject in terms you can understand without a backgroundin statistics or natural language processing. Examples arein Java, but the concepts can be applied in any language. Written for Java developers, the book requires no prior knowledge of GWT. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. Winner of 2013 Jolt Awards: The Best Books—one of five notable books every serious programmer should read. What's Inside When to use text-taming techniques Important open-source libraries like Solr and Mahout How to build text-processing applications About the Authors Grant Ingersoll is an engineer, speaker, and trainer, a Lucenecommitter, and a cofounder of the Mahout machine-learning project. Thomas Morton is the primary developer of OpenNLP and Maximum Entropy. Drew Farris is a technology consultant, software developer, and contributor to Mahout,Lucene, and Solr. "Takes the mystery out of verycomplex processes."—From the Foreword by Liz Liddy, Dean, iSchool, Syracuse University Table of Contents Getting started taming text Foundations of taming text Searching Fuzzy string matching Identifying people, places, and things Clustering text Classification, categorization, and tagging Building an example question answering system Untamed text: exploring the next frontier

Machine Learning Bookcamp

Author : Alexey Grigorev
Publisher : Simon and Schuster
ISBN 13 : 1617296813
Total Pages : 470 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis Machine Learning Bookcamp by : Alexey Grigorev

Download or read book Machine Learning Bookcamp written by Alexey Grigorev and published by Simon and Schuster. This book was released on 2021-11-23 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: The only way to learn is to practice! In Machine Learning Bookcamp, you''ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you''ve learned in previous chapters. By the end of the bookcamp, you''ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technology Machine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that''s exactly what you''ll be doing in Machine Learning Bookcamp. about the book In Machine Learning Bookcamp you''ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you''ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You''ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you''re done working through these fun and informative projects, you''ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what''s inside Code fundamental ML algorithms from scratch Collect and clean data for training models Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images and text Deploy ML models to a production-ready environment about the reader For readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.

Elephant Run

Author : Roland Smith
Publisher : Perfection Learning
ISBN 13 : 9781606865156
Total Pages : 0 pages
Book Rating : 4.8/5 (651 download)

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Book Synopsis Elephant Run by : Roland Smith

Download or read book Elephant Run written by Roland Smith and published by Perfection Learning. This book was released on 2009-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: When 14-year-old Nick is sent to his father in Burma to escape the 1941 bombings in London, he finds himself in even more danger as Japanese soldiers arrive and take control of the plantation house.

Practical Machine Learning

Author : Ted Dunning
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491915722
Total Pages : 55 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Practical Machine Learning by : Ted Dunning

Download or read book Practical Machine Learning written by Ted Dunning and published by "O'Reilly Media, Inc.". This book was released on 2014 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Building a simple but powerful recommendation system is much easier than you think. Approachable for all levels of expertise, this report explains innovations that make machine learning practical for business production settingsand demonstrates how even a small-scale development team can design an effective large-scale recommendation system. Apache Mahout committers Ted Dunning and Ellen Friedman walk you through a design that relies on careful simplification. Youll learn how to collect the right data, analyze it with an algorithm from the Mahout library, and then easily deploy the recommender using search technology, such as Apache Solr or Elasticsearch. Powerful and effective, this efficient combination does learning offline and delivers rapid response recommendations in real time. Understand the tradeoffs between simple and complex recommendersCollect user data that tracks user actionsrather than their ratingsPredict what a user wants based on behavior by others, using Mahoutfor co-occurrence analysisUse search technology to offer recommendations in real time, complete with item metadataWatch the recommender in action with a music service exampleImprove your recommender with dithering, multimodal recommendation, and other techniques.

Practical Machine Learning

Author : Sunila Gollapudi
Publisher : Packt Publishing Ltd
ISBN 13 : 1784394017
Total Pages : 468 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis Practical Machine Learning by : Sunila Gollapudi

Download or read book Practical Machine Learning written by Sunila Gollapudi and published by Packt Publishing Ltd. This book was released on 2016-01-30 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniques About This Book Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark Comprehensive practical solutions taking you into the future of machine learning Go a step further and integrate your machine learning projects with Hadoop Who This Book Is For This book has been created for data scientists who want to see machine learning in action and explore its real-world application. With guidance on everything from the fundamentals of machine learning and predictive analytics to the latest innovations set to lead the big data revolution into the future, this is an unmissable resource for anyone dedicated to tackling current big data challenges. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately. What You Will Learn Implement a wide range of algorithms and techniques for tackling complex data Get to grips with some of the most powerful languages in data science, including R, Python, and Julia Harness the capabilities of Spark and Hadoop to manage and process data successfully Apply the appropriate machine learning technique to address real-world problems Get acquainted with Deep learning and find out how neural networks are being used at the cutting-edge of machine learning Explore the future of machine learning and dive deeper into polyglot persistence, semantic data, and more In Detail Finding meaning in increasingly larger and more complex datasets is a growing demand of the modern world. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. Machine learning uses complex algorithms to make improved predictions of outcomes based on historical patterns and the behaviour of data sets. Machine learning can deliver dynamic insights into trends, patterns, and relationships within data, immensely valuable to business growth and development. This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big data. This is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application. With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data. You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naive Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies. Style and approach A practical data science tutorial designed to give you an insight into the practical application of machine learning, this book takes you through complex concepts and tasks in an accessible way. Featuring information on a wide range of data science techniques, Practical Machine Learning is a comprehensive data science resource.

Collective Intelligence in Action

Author : Satnam Alag
Publisher : Simon and Schuster
ISBN 13 : 163835538X
Total Pages : 609 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Collective Intelligence in Action by : Satnam Alag

Download or read book Collective Intelligence in Action written by Satnam Alag and published by Simon and Schuster. This book was released on 2008-09-30 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once? Identifying the wants, needs, and knowledge of internet users can be like listening to a mob. In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence--locked in the data people leave behind as they surf websites, post blogs, and interact with other users. Collective Intelligence in Action is a hands-on guidebook for implementing collective intelligence concepts using Java. It is the first Java-based book to emphasize the underlying algorithms and technical implementation of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches. This book is for Java developers implementing Collective Intelligence in real, high-use applications. Following a running example in which you harvest and use information from blogs, you learn to develop software that you can embed in your own applications. The code examples are immediately reusable and give the Java developer a working collective intelligence toolkit. Along the way, you work with, a number of APIs and open-source toolkits including text analysis and search using Lucene, web-crawling using Nutch, and applying machine learning algorithms using WEKA and the Java Data Mining (JDM) standard. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

Of Six Mediaeval Women

Author : Alice Kemp-Welch
Publisher :
ISBN 13 :
Total Pages : 290 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Of Six Mediaeval Women by : Alice Kemp-Welch

Download or read book Of Six Mediaeval Women written by Alice Kemp-Welch and published by . This book was released on 1913 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Tusk and Stone

Author : Malcolm Joseph Bosse
Publisher :
ISBN 13 : 9781886910744
Total Pages : 0 pages
Book Rating : 4.9/5 (17 download)

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Book Synopsis Tusk and Stone by : Malcolm Joseph Bosse

Download or read book Tusk and Stone written by Malcolm Joseph Bosse and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: After a criminal gang attacks his caravan and he loses his identity as a Brahmin, Arjun resigns himself to his new life as a soldier, becomes an elephant driver, and searches for his kidnapped sister. At the height of his fame he is captured again, and as a slave once more, finds unexpected fulfillment as a stone carver.

Machine Learning Algorithms

Author : Giuseppe Bonaccorso
Publisher : Packt Publishing Ltd
ISBN 13 : 1785884514
Total Pages : 352 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Machine Learning Algorithms by : Giuseppe Bonaccorso

Download or read book Machine Learning Algorithms written by Giuseppe Bonaccorso and published by Packt Publishing Ltd. This book was released on 2017-07-24 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn Acquaint yourself with important elements of Machine Learning Understand the feature selection and feature engineering process Assess performance and error trade-offs for Linear Regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector machines Implement clusters to a dataset Explore the concept of Natural Processing Language and Recommendation Systems Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.

Tua and the Elephant

Author : R.P. Harris
Publisher : Chronicle Books
ISBN 13 : 1452116539
Total Pages : 206 pages
Book Rating : 4.4/5 (521 download)

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Book Synopsis Tua and the Elephant by : R.P. Harris

Download or read book Tua and the Elephant written by R.P. Harris and published by Chronicle Books. This book was released on 2012-04-06 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ten-year-old Tua—Thai for "peanut"—has everything she needs at home in Chiang Mai, Thailand, except for one thing she's always wanted: a sister. In the market one day, Tua makes an accidental acquaintance—one with wise, loving eyes, remarkable strength, and a very curious trunk. And when Tua meets Pohn-Pohn, it's clear this elephant needs her help. Together, the unusual team sets off on a remarkable journey to escape from Pohn-Pohn's vile captors. From the bustling night market to the hallowed halls of a Buddhist temple and finally, to the sanctuary of an elephant refuge, this clever girl and her beloved companion find that right under their noses is exactly what each has been searching for: a friend.

Hadoop in Practice

Author : Alex Holmes
Publisher : Manning Publications
ISBN 13 : 9781617292224
Total Pages : 512 pages
Book Rating : 4.2/5 (922 download)

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Book Synopsis Hadoop in Practice by : Alex Holmes

Download or read book Hadoop in Practice written by Alex Holmes and published by Manning Publications. This book was released on 2014-10-12 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Hadoop in Practice, Second Edition provides over 100 tested, instantly useful techniques that will help you conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN and integrating Kafka, Impala, and Spark SQL with Hadoop. You'll also get new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book It's always a good time to upgrade your Hadoop skills! Hadoop in Practice, Second Edition provides a collection of 104 tested, instantly useful techniques for analyzing real-time streams, moving data securely, machine learning, managing large-scale clusters, and taming big data using Hadoop. This completely revised edition covers changes and new features in Hadoop core, including MapReduce 2 and YARN. You'll pick up hands-on best practices for integrating Spark, Kafka, and Impala with Hadoop, and get new and updated techniques for the latest versions of Flume, Sqoop, and Mahout. In short, this is the most practical, up-to-date coverage of Hadoop available. Readers need to know a programming language like Java and have basic familiarity with Hadoop. What's Inside Thoroughly updated for Hadoop 2 How to write YARN applications Integrate real-time technologies like Storm, Impala, and Spark Predictive analytics using Mahout and RR Readers need to know a programming language like Java and have basic familiarity with Hadoop. About the Author Alex Holmes works on tough big-data problems. He is a software engineer, author, speaker, and blogger specializing in large-scale Hadoop projects. Table of Contents PART 1 BACKGROUND AND FUNDAMENTALS Hadoop in a heartbeat Introduction to YARN PART 2 DATA LOGISTICS Data serialization—working with text and beyond Organizing and optimizing data in HDFS Moving data into and out of Hadoop PART 3 BIG DATA PATTERNS Applying MapReduce patterns to big data Utilizing data structures and algorithms at scale Tuning, debugging, and testing PART 4 BEYOND MAPREDUCE SQL on Hadoop Writing a YARN application

Gentlemen of the Road

Author : Michael Chabon
Publisher : Del Rey
ISBN 13 : 0307495655
Total Pages : 178 pages
Book Rating : 4.3/5 (74 download)

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Book Synopsis Gentlemen of the Road by : Michael Chabon

Download or read book Gentlemen of the Road written by Michael Chabon and published by Del Rey. This book was released on 2008-12-18 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: #1 SAN FRANCISCO CHRONICLE BESTSELLER • NAMED ONE OF THE BEST BOOKS OF THE YEAR BY THE CHICAGO TRIBUNE “A picaresque, swashbuckling adventure.”—The Washington Post Book World They’re an odd pair, to be sure: pale, rail-thin, black-clad Zelikman, a moody, itinerant physician fond of jaunty headgear, and ex-soldier Amram, a gray-haired giant of a man as quick with a razor-tongued witticism as with a sharpened battle-ax. Brothers under the skin, comrades in arms, they make their rootless way through the Caucasus Mountains, circa a.d. 950, living as they please and surviving however they can—as blades and thieves for hire and as practiced bamboozlers, cheerfully separating the gullible from their money. But when they are dragooned into service as escorts and defenders to a prince of the Khazar Empire, they soon find themselves the half-willing generals in a full-scale revolution—on a road paved with warriors and whores, evil emperors and extraordinary elephants, secrets, swordplay, and such stuff as the grandest adventures are made of. Praise for Gentlemen of the Road “Within a few pages I was happily tangled in [Chabon’s] net of finely filigreed language, seduced by an old-school-style swashbuckling quest . . . laced with surprises and humor.”—San Francisco Chronicle “[Chabon] is probably the premiere prose stylist—the Updike—of his generation.”—Time “The action is intricate and exuberant. . . . It’s hard to resist its gathering momentum, not to mention the sheer headlong pleasure of Chabon’s language.”—The New York Times Book Review “[A] wild, wild adventure . . . abounds with lush language . . . This book roars to be read aloud.”—Chicago Sun-Times