Apache Mahout Essentials

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1783555009
Total Pages : 165 pages
Book Rating : 4.7/5 (835 download)

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Book Synopsis Apache Mahout Essentials by : Jayani Withanawasam

Download or read book Apache Mahout Essentials written by Jayani Withanawasam and published by Packt Publishing Ltd. This book was released on 2015-06-19 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apache Mahout is a scalable machine learning library with algorithms for clustering, classification, and recommendations. It empowers users to analyze patterns in large, diverse, and complex datasets faster and more scalably. This book is an all-inclusive guide to analyzing large and complex datasets using Apache Mahout. It explains complicated but very effective machine learning algorithms simply, in relation to real-world practical examples. Starting from the fundamental concepts of machine learning and Apache Mahout, this book guides you through Apache Mahout's implementations of machine learning techniques including classification, clustering, and recommendations. During this exciting walkthrough, real-world applications, a diverse range of popular algorithms and their implementations, code examples, evaluation strategies, and best practices are given for each technique. Finally, you will learn vdata visualization techniques for Apache Mahout to bring your data to life.

Apache Mahout Clustering Designs

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Publisher : Packt Publishing Ltd
ISBN 13 : 1783284447
Total Pages : 131 pages
Book Rating : 4.7/5 (832 download)

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Book Synopsis Apache Mahout Clustering Designs by : Ashish Gupta

Download or read book Apache Mahout Clustering Designs written by Ashish Gupta and published by Packt Publishing Ltd. This book was released on 2015-10-08 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore clustering algorithms used with Apache Mahout About This Book Use Mahout for clustering datasets and gain useful insights Explore the different clustering algorithms used in day-to-day work A practical guide to create and evaluate your own clustering models using real world data sets Who This Book Is For This book is for developers who want to try out clustering on large datasets using Mahout. It will also be useful for those users who don't have background in Mahout, but have knowledge of basic programming and are familiar with basics of machine learning and clustering. It will be helpful if you know about clustering techniques with some other tool. What You Will Learn Explore clustering algorithms and cluster evaluation techniques Learn different types of clustering and distance measuring techniques Perform clustering on your data using K-Means clustering Discover how canopy clustering is used as pre-process step for K-Means Use the Fuzzy K-Means algorithm in Apache Mahout Implement Streaming K-Means clustering in Mahout Learn Spectral K-Means clustering implementation of Mahout In Detail As more and more organizations are discovering the use of big data analytics, interest in platforms that provide storage, computation, and analytic capabilities has increased. Apache Mahout caters to this need and paves the way for the implementation of complex algorithms in the field of machine learning to better analyse your data and get useful insights into it. Starting with the introduction of clustering algorithms, this book provides an insight into Apache Mahout and different algorithms it uses for clustering data. It provides a general introduction of the algorithms, such as K-Means, Fuzzy K-Means, StreamingKMeans, and how to use Mahout to cluster your data using a particular algorithm. You will study the different types of clustering and learn how to use Apache Mahout with real world data sets to implement and evaluate your clusters. This book will discuss about cluster improvement and visualization using Mahout APIs and also explore model-based clustering and topic modelling using Dirichlet process. Finally, you will learn how to build and deploy a model for production use. Style and approach This book is a hand's-on guide with examples using real-world datasets. Each chapter begins by explaining the algorithm in detail and follows up with showing how to use mahout for that algorithm using example data-sets.

Hadoop Essentials

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Publisher : Packt Publishing Ltd
ISBN 13 : 1784390461
Total Pages : 194 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis Hadoop Essentials by : Shiva Achari

Download or read book Hadoop Essentials written by Shiva Achari and published by Packt Publishing Ltd. This book was released on 2015-04-29 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a system or application developer interested in learning how to solve practical problems using the Hadoop framework, then this book is ideal for you. This book is also meant for Hadoop professionals who want to find solutions to the different challenges they come across in their Hadoop projects.

HDInsight Essentials - Second Edition

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Publisher : Packt Publishing Ltd
ISBN 13 : 1784396664
Total Pages : 179 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis HDInsight Essentials - Second Edition by : Rajesh Nadipalli

Download or read book HDInsight Essentials - Second Edition written by Rajesh Nadipalli and published by Packt Publishing Ltd. This book was released on 2015-01-27 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to discover one of the latest tools designed to produce stunning Big Data insights, this book features everything you need to get to grips with your data. Whether you are a data architect, developer, or a business strategist, HDInsight adds value in everything from development, administration, and reporting.

Apache Hive Essentials

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Publisher : Packt Publishing Ltd
ISBN 13 : 1789136512
Total Pages : 203 pages
Book Rating : 4.7/5 (891 download)

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Book Synopsis Apache Hive Essentials by : Dayong Du

Download or read book Apache Hive Essentials written by Dayong Du and published by Packt Publishing Ltd. This book was released on 2018-06-30 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes you on a fantastic journey to discover the attributes of big data using Apache Hive. Key Features Grasp the skills needed to write efficient Hive queries to analyze the Big Data Discover how Hive can coexist and work with other tools within the Hadoop ecosystem Uses practical, example-oriented scenarios to cover all the newly released features of Apache Hive 2.3.3 Book Description In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment. Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey. By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems What you will learn Create and set up the Hive environment Discover how to use Hive's definition language to describe data Discover interesting data by joining and filtering datasets in Hive Transform data by using Hive sorting, ordering, and functions Aggregate and sample data in different ways Boost Hive query performance and enhance data security in Hive Customize Hive to your needs by using user-defined functions and integrate it with other tools Who this book is for If you are a data analyst, developer, or simply someone who wants to quickly get started with Hive to explore and analyze Big Data in Hadoop, this is the book for you. Since Hive is an SQL-like language, some previous experience with SQL will be useful to get the most out of this book.

Learning Apache Mahout Classification

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Author :
Publisher : Packt Pub Limited
ISBN 13 : 9781783554959
Total Pages : 130 pages
Book Rating : 4.5/5 (549 download)

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Book Synopsis Learning Apache Mahout Classification by : Ashish Gupta

Download or read book Learning Apache Mahout Classification written by Ashish Gupta and published by Packt Pub Limited. This book was released on 2015-02-26 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation If you are a data scientist who has some experience with the Hadoop ecosystem and machine learning methods and want to try out classification on large datasets using Mahout, this book is ideal for you. Knowledge of Java is essential.

Building Python Real-Time Applications with Storm

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Publisher : Packt Publishing Ltd
ISBN 13 : 1784392871
Total Pages : 122 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis Building Python Real-Time Applications with Storm by : Kartik Bhatnagar

Download or read book Building Python Real-Time Applications with Storm written by Kartik Bhatnagar and published by Packt Publishing Ltd. This book was released on 2015-12-02 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to process massive real-time data streams using Storm and Python—no Java required! About This Book Learn to use Apache Storm and the Python Petrel library to build distributed applications that process large streams of data Explore sample applications in real-time and analyze them in the popular NoSQL databases MongoDB and Redis Discover how to apply software development best practices to improve performance, productivity, and quality in your Storm projects Who This Book Is For This book is intended for Python developers who want to benefit from Storm's real-time data processing capabilities. If you are new to Python, you'll benefit from the attention to key supporting tools and techniques such as automated testing, virtual environments, and logging. If you're an experienced Python developer, you'll appreciate the thorough and detailed examples What You Will Learn Install Storm and learn about the prerequisites Get to know the components of a Storm topology and how to control the flow of data between them Ingest Twitter data directly into Storm Use Storm with MongoDB and Redis Build topologies and run them in Storm Use an interactive graphical debugger to debug your topology as it's running in Storm Test your topology components outside of Storm Configure your topology using YAML In Detail Big data is a trending concept that everyone wants to learn about. With its ability to process all kinds of data in real time, Storm is an important addition to your big data “bag of tricks.” At the same time, Python is one of the fastest-growing programming languages today. It has become a top choice for both data science and everyday application development. Together, Storm and Python enable you to build and deploy real-time big data applications quickly and easily. You will begin with some basic command tutorials to set up storm and learn about its configurations in detail. You will then go through the requirement scenarios to create a Storm cluster. Next, you'll be provided with an overview of Petrel, followed by an example of Twitter topology and persistence using Redis and MongoDB. Finally, you will build a production-quality Storm topology using development best practices. Style and approach This book takes an easy-to-follow and a practical approach to help you understand all the concepts related to Storm and Python.

Mastering Machine Learning with R

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Publisher : Packt Publishing Ltd
ISBN 13 : 1783984538
Total Pages : 400 pages
Book Rating : 4.7/5 (839 download)

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Book Synopsis Mastering Machine Learning with R by : Cory Lesmeister

Download or read book Mastering Machine Learning with R written by Cory Lesmeister and published by Packt Publishing Ltd. This book was released on 2015-10-28 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master machine learning techniques with R to deliver insights for complex projects About This Book Get to grips with the application of Machine Learning methods using an extensive set of R packages Understand the benefits and potential pitfalls of using machine learning methods Implement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful. What You Will Learn Gain deep insights to learn the applications of machine learning tools to the industry Manipulate data in R efficiently to prepare it for analysis Master the skill of recognizing techniques for effective visualization of data Understand why and how to create test and training data sets for analysis Familiarize yourself with fundamental learning methods such as linear and logistic regression Comprehend advanced learning methods such as support vector machines Realize why and how to apply unsupervised learning methods In Detail Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series. The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages. Style and approach This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.

Essential Cybersecurity Science

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491921064
Total Pages : 193 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Essential Cybersecurity Science by : Josiah Dykstra

Download or read book Essential Cybersecurity Science written by Josiah Dykstra and published by "O'Reilly Media, Inc.". This book was released on 2015-12-08 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’re involved in cybersecurity as a software developer, forensic investigator, or network administrator, this practical guide shows you how to apply the scientific method when assessing techniques for protecting your information systems. You’ll learn how to conduct scientific experiments on everyday tools and procedures, whether you’re evaluating corporate security systems, testing your own security product, or looking for bugs in a mobile game. Once author Josiah Dykstra gets you up to speed on the scientific method, he helps you focus on standalone, domain-specific topics, such as cryptography, malware analysis, and system security engineering. The latter chapters include practical case studies that demonstrate how to use available tools to conduct domain-specific scientific experiments. Learn the steps necessary to conduct scientific experiments in cybersecurity Explore fuzzing to test how your software handles various inputs Measure the performance of the Snort intrusion detection system Locate malicious “needles in a haystack” in your network and IT environment Evaluate cryptography design and application in IoT products Conduct an experiment to identify relationships between similar malware binaries Understand system-level security requirements for enterprise networks and web services

From Data to Discovery: The Essential Guide to Big Data Analytics

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Publisher : SK Research Group of Companies
ISBN 13 : 8119980808
Total Pages : 261 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis From Data to Discovery: The Essential Guide to Big Data Analytics by : Dr.J.Premalatha

Download or read book From Data to Discovery: The Essential Guide to Big Data Analytics written by Dr.J.Premalatha and published by SK Research Group of Companies. This book was released on 2024-02-27 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr.J.Premalatha, Vice Principal, Dhanalakshmi Srinivasan Arts and Science(Co-Ed) College, Mamallapuram, Chennai, Tamil Nadu, India. Dr.K.Kalaiselvi, Professor, Department of Data Analytics, Saveetha College of Liberal Arts and Sciences, SIMATS, Chennai, Tamil Nadu, India. Dr.A.Senthilkumar, Assistant Professor, Department of Computer Science with Data Analytics, Sri Ramakrishna College of Arts & Science, Coimbatore, Tamil Nadu, India.

Multidisciplinary International Conference on Innovations in Education Science & Technology ICIEST-2023

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Author :
Publisher : GEH PRESS
ISBN 13 :
Total Pages : 393 pages
Book Rating : 4.9/5 (898 download)

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Book Synopsis Multidisciplinary International Conference on Innovations in Education Science & Technology ICIEST-2023 by : Prof. (Dr.) B.K Sarkar

Download or read book Multidisciplinary International Conference on Innovations in Education Science & Technology ICIEST-2023 written by Prof. (Dr.) B.K Sarkar and published by GEH PRESS . This book was released on 2023-12-15 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: The central motive of the International Conference is to throw up a number of new ideas and solutions to address the present-day challenges in the fields of 1: Science, Technology, Engineering and Mathematics. 2: Economics / Accounts. 3: Architecture and Design, Business, Divinity, Education, Engineering, Environmental Studies and Forestry, Family and Consumer Science, Health Sciences ,Human Physical Performance and Recreation, Journalism, Media Studies and Communication ,Law ,Library and Museum Studies ,Military Sciences ,Public Administration ,Social Work ,Transportation, Fine arts, Agricultural education, Management ,Social sciences , Physics, Chemistry, Business and commerce. 4: Health oriented education, Medical, Pharmacy, Dentel, Ayurveda, and Yoga. 5: English, Regional Language(s), Maths, Science, Social Sciences, Physical Education Computer Basics, Arts (Drawing) 6: History, Languages and linguistics, Literature, Performing arts, Philosophy, Religion and Religious studies, Visual arts. 7: Anthropology, Archaeology, Area Studies, Cultural and Ethnic Studies, Economics Gender and Sexuality Studies, Geography, Political Science, Psychology, Sociology. 8: Chemistry, Earth Sciences, Life Sciences, Physics, Space Sciences. 9: Computer Sciences, Logic, Mathematics, Statistics, Systems Science. The scope of the conference is broad and covers many aspects of international research prospective. This conference aims to provide a scholarly platform for participants to publish their research in reputed International Journals. The authors have incredible opportunity to present/5- Minute Video their research virtually and present findings worldwide that will not only help them gain the necessary exposure that they need to make their research work known in global scientific circles but also open the door to incredible opportunities for collaboration and conducting further research.

International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018

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Author :
Publisher : Springer
ISBN 13 : 3030031462
Total Pages : 1590 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018 by : Jude Hemanth

Download or read book International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018 written by Jude Hemanth and published by Springer. This book was released on 2018-12-20 with total page 1590 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses data communication and computer networking, communication technologies and the applications of IoT (Internet of Things), big data, cloud computing and healthcare informatics. It explores, examines and critiques intelligent data communications and presents inventive methodologies in communication technologies and IoT. Aimed at researchers and academicians who need to understand the importance of data communication and advanced technologies in IoT, it offers different perspectives to help readers increase their knowledge and motivates them to conduct research in the area, highlighting various innovative ideas for future research.

Mahout in Action

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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

Handbook of Research on Big Data Storage and Visualization Techniques

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Author :
Publisher : IGI Global
ISBN 13 : 1522531432
Total Pages : 1078 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Big Data Storage and Visualization Techniques by : Segall, Richard S.

Download or read book Handbook of Research on Big Data Storage and Visualization Techniques written by Segall, Richard S. and published by IGI Global. This book was released on 2018-01-05 with total page 1078 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.

Knowledge Discovery in Big Data from Astronomy and Earth Observation

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Author :
Publisher : Elsevier
ISBN 13 : 0128191546
Total Pages : 472 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Knowledge Discovery in Big Data from Astronomy and Earth Observation by : Petr Skoda

Download or read book Knowledge Discovery in Big Data from Astronomy and Earth Observation written by Petr Skoda and published by Elsevier. This book was released on 2020-04-23 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants. Addresses both astronomy and geosciences in parallel, from a big data perspective Includes introductory information, key principles, applications and the latest techniques Well-supported by computing and information science-oriented chapters to introduce the necessary knowledge in these fields

Data Science Quick Reference Manual - Advanced Machine Learning and Deployment

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Author :
Publisher : Mario Capurso
ISBN 13 :
Total Pages : 278 pages
Book Rating : 4./5 ( download)

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Book Synopsis Data Science Quick Reference Manual - Advanced Machine Learning and Deployment by : Mario A. B. Capurso

Download or read book Data Science Quick Reference Manual - Advanced Machine Learning and Deployment written by Mario A. B. Capurso and published by Mario Capurso. This book was released on 2023-09-08 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work follows the 2021 curriculum of the Association for Computing Machinery for specialists in Data Sciences, with the aim of producing a manual that collects notions in a simplified form, facilitating a personal training path starting from specialized skills in Computer Science or Mathematics or Statistics. It has a bibliography with links to quality material but freely usable for your own training and contextual practical exercises. Part in a series of texts, it first summarizes the standard CRISP DM working methodology used in this work and in Data Science projects. As this text uses Orange for the application aspects, it describes its installation and widgets. The data modeling phase is considered from the perspective of machine learning by summarizing machine learning types, model types, problem types, and algorithm types. Advanced aspects associated with modeling are described such as loss and optimization functions such as gradient descent, techniques to analyze model performance such as Bootstrapping and Cross Validation. Deployment scenarios and the most common platforms are analyzed, with application examples. Mechanisms are proposed to automate machine learning and to support the interpretability of models and results such as Partial Dependence Plot, Permuted Feature Importance and others. The exercises are described with Orange and Python using the Keras/Tensorflow library. The text is accompanied by supporting material and it is possible to download the examples and the test data.

Deep Learning: Practical Neural Networks with Java

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Publisher : Packt Publishing Ltd
ISBN 13 : 1788471717
Total Pages : 744 pages
Book Rating : 4.7/5 (884 download)

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Book Synopsis Deep Learning: Practical Neural Networks with Java by : Yusuke Sugomori

Download or read book Deep Learning: Practical Neural Networks with Java written by Yusuke Sugomori and published by Packt Publishing Ltd. This book was released on 2017-06-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build and run intelligent applications by leveraging key Java machine learning libraries About This Book Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries. Explore a broad variety of data processing, machine learning, and natural language processing through diagrams, source code, and real-world applications This step-by-step guide will help you solve real-world problems and links neural network theory to their application Who This Book Is For This course is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life. What You Will Learn Get a practical deep dive into machine learning and deep learning algorithms Explore neural networks using some of the most popular Deep Learning frameworks Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts, algorithms, and the toolbox for deep learning Select and split data sets into training, test, and validation, and explore validation strategies Apply the code generated in practical examples, including weather forecasting and pattern recognition In Detail Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work. The course provides you with highly practical content explaining deep learning with Java, from the following Packt books: Java Deep Learning Essentials Machine Learning in Java Neural Network Programming with Java, Second Edition Style and approach This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java with other de facto components to get the most out of it. Through this comprehensive course, you'll learn the basics of predictive modelling and progress to solve real-world problems and links neural network theory to their application