Ix Developer Machine Learning
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Ix Developer Machine Learning
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Author : iX Developer
language : de
Publisher: Heise Medien
Release Date : 2020-12-05
Ix Developer Machine Learning written by iX Developer and has been published by Heise Medien this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-05 with Computers categories.
Machine Learning hat in den letzten Jahren so rasante technische Fortschritte gemacht wie kaum ein anderer Bereich der IT. Zahlreiche Open-Source-Werkzeuge stehen Entwicklerinnen und Entwicklern zur Verfügung. Neben den Frameworks wie TensorFlow und PyTorch existieren konkrete Methoden für spezifische Anwendungsbereiche wie BERT und Word2vec bei der Textanalyse oder YOLO zur Objektdetektion. Das iX-Developer-Sonderheft "Machine Learning: Bessere Modelle, produktiver Einsatz" trägt der rasanten Entwicklung als Fortführung des Machine-Learning-Sonderhefts von 2018 Rechnung. Es beleuchtet die jüngsten Entwicklungen im Bereich der großen Frameworks, der Data-Science-Bibliotheken von Python sowie zahlreiche Methoden und Algorithmen. Das Heft bietet vor allem einen breiten Praxisteil mit konkreten Anwendungen in der Textanalyse und für die Zeitreihenvorhersage sowie mit einem dreiteiligen Tutorial zur Bildanalyse.
Ix Developer 2018 Machine Learning
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Author : iX-Redaktion
language : de
Publisher: Heise Medien GmbH & Co. KG
Release Date : 2018-11-29
Ix Developer 2018 Machine Learning written by iX-Redaktion and has been published by Heise Medien GmbH & Co. KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-29 with Computers categories.
In der neuen Developer-Spezialausgabe der iX dreht sich alles um das Thema Machine Learning: Angefangen bei der Historie der Disziplin über detaillierte Betrachtungen der unterschiedlichen Frameworks und verwendeten Programmiersprachen bis hin zu Praxisbeispielen zur Textanalyse, Bilderkennung und vielem mehr. Wagen Sie mit unseren Autoren einen Blick in die Blackbox des Zukunftsthemas und lernen sie neben den technischen Anwendungen und Voraussetzungen auch, welche ethische und rechtlichen Bedenken die Themen Künstliche Intelligenz und Maschinelles Lernen mit sich bringen.
Machine Learning
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Author : Jason Bell
language : en
Publisher: John Wiley & Sons
Release Date : 2014-11-03
Machine Learning written by Jason Bell 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 2014-11-03 with Mathematics categories.
Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference. At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data. Machine Learning is an accessible, comprehensive guide for the non-mathematician, providing clear guidance that allows readers to: Learn the languages of machine learning including Hadoop, Mahout, and Weka Understand decision trees, Bayesian networks, and artificial neural networks Implement Association Rule, Real Time, and Batch learning Develop a strategic plan for safe, effective, and efficient machine learning By learning to construct a system that can learn from data, readers can increase their utility across industries. Machine learning sits at the core of deep dive data analysis and visualization, which is increasingly in demand as companies discover the goldmine hiding in their existing data. For the tech professional involved in data science, Machine Learning: Hands-On for Developers and Technical Professionals provides the skills and techniques required to dig deeper.
Building Machine Learning And Deep Learning Models On Google Cloud Platform
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Author : Ekaba Bisong
language : en
Publisher: Apress
Release Date : 2019-09-27
Building Machine Learning And Deep Learning Models On Google Cloud Platform written by Ekaba Bisong and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-27 with Computers categories.
Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers
Practical Machine Learning With H2o
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Author : Darren Cook
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-12-05
Practical Machine Learning With H2o written by Darren Cook 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 2016-12-05 with Computers categories.
Machine learning has finally come of age. With H2O software, you can perform machine learning and data analysis using a simple open source framework that’s easy to use, has a wide range of OS and language support, and scales for big data. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. If you’re familiar with R or Python, know a bit of statistics, and have some experience manipulating data, author Darren Cook will take you through H2O basics and help you conduct machine-learning experiments on different sample data sets. You’ll explore several modern machine-learning techniques such as deep learning, random forests, unsupervised learning, and ensemble learning. Learn how to import, manipulate, and export data with H2O Explore key machine-learning concepts, such as cross-validation and validation data sets Work with three diverse data sets, including a regression, a multinomial classification, and a binomial classification Use H2O to analyze each sample data set with four supervised machine-learning algorithms Understand how cluster analysis and other unsupervised machine-learning algorithms work
Ix Developer 2020
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Author : IX-Redaktion
language : de
Publisher: Heise Medien
Release Date : 2020-08-25
Ix Developer 2020 written by IX-Redaktion and has been published by Heise Medien this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-25 with Computers categories.
So wie ein schönes und stabiles Haus einen guten Architekten braucht, steht hinter stabiler und funktionaler Software ein guter Softwarearchitekt. Im neuen iX Developer "Moderne Softwarearchitekturen" geben erfahrene Softwarearchitekten einen umfassenden Überblick zu den Grundlagen und aktuellen Trends der Softwarearchitektur. Ob Domain Driven Design oder Microservice-Architekturen, ob Cloud-native Entwicklung oder Service Meshes in Containerumgebungen – Softwareentwickler finden hier vielfältige Anregungen, wie sich die komplexen Aufgaben in unterschiedlichsten Gebieten meistern lassen. Ein Schwerpunkt des Heftes liegt auf der Qualitätssicherung – vom Requirements Engineering über die Testautomatisierung und Reviews bis zur Performance-Analyse. Dabei kommen auch jüngere Entwicklungen wie Shift Left oder Documentation as Code zur Sprache. Schließlich wirft das iX Developer "Moderne Softwarearchitekturen" auch einen Blick über den Tellerrand und beleuchtet übergreifende Themen wie Ethik der Softwareentwicklung, Methoden zur Verbesserung der User Experience, KI und Quantencomputing.
Machine Learning For Developers
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Author : Rodolfo Bonnin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-10-26
Machine Learning For Developers written by Rodolfo Bonnin 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 2017-10-26 with Computers categories.
Your one-stop guide to becoming a Machine Learning expert. About This Book Learn to develop efficient and intelligent applications by leveraging the power of Machine Learning A highly practical guide explaining the concepts of problem solving in the easiest possible manner Implement Machine Learning in the most practical way Who This Book Is For This book will appeal to any developer who wants to know what Machine Learning is and is keen to use Machine Learning to make their day-to-day apps fast, high performing, and accurate. Any developer who wants to enter the field of Machine Learning can effectively use this book as an entry point. What You Will Learn Learn the math and mechanics of Machine Learning via a developer-friendly approach Get to grips with widely used Machine Learning algorithms/techniques and how to use them to solve real problems Get a feel for advanced concepts, using popular programming frameworks. Prepare yourself and other developers for working in the new ubiquitous field of Machine Learning Get an overview of the most well known and powerful tools, to solve computing problems using Machine Learning. Get an intuitive and down-to-earth introduction to current Machine Learning areas, and apply these concepts on interesting and cutting-edge problems. In Detail Most of us have heard about the term Machine Learning, but surprisingly the question frequently asked by developers across the globe is, “How do I get started in Machine Learning?”. One reason could be attributed to the vastness of the subject area because people often get overwhelmed by the abstractness of ML and terms such as regression, supervised learning, probability density function, and so on. This book is a systematic guide teaching you how to implement various Machine Learning techniques and their day-to-day application and development. You will start with the very basics of data and mathematical models in easy-to-follow language that you are familiar with; you will feel at home while implementing the examples. The book will introduce you to various libraries and frameworks used in the world of Machine Learning, and then, without wasting any time, you will get to the point and implement Regression, Clustering, classification, Neural networks, and more with fun examples. As you get to grips with the techniques, you'll learn to implement those concepts to solve real-world scenarios for ML applications such as image analysis, Natural Language processing, and anomaly detections of time series data. By the end of the book, you will have learned various ML techniques to develop more efficient and intelligent applications. Style and approach This book gives you a glimpse of Machine Learning Models and the application of models at scale using clustering, classification, regression and reinforcement learning with fun examples. Hands-on examples will be presented to understand the power of problem solving with Machine Learning and Advanced architectures, software installation, and configuration.
Research And Development In Expert Systems Ix
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Author : British Computer Society. Specialist Group on Expert Systems. Technical Conference
language : en
Publisher: Cambridge University Press
Release Date : 1993-02-04
Research And Development In Expert Systems Ix written by British Computer Society. Specialist Group on Expert Systems. Technical Conference and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-02-04 with Computers categories.
This volume contains the refereed and invited papers which were presented at Expert Systems 92, the twelfth annual conference of the British Computer Society's Specialist Group on Expert Systems, held in Cambridge in December 1992. Together with its predecessors this is essential reading for those who wish to keep up-to-date with developments and opportunities in this important field.
Natural Language Processing With Pytorch
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Author : Delip Rao
language : en
Publisher: O'Reilly Media
Release Date : 2019-01-22
Natural Language Processing With Pytorch written by Delip Rao and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-22 with Computers categories.
Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems
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.