Fundamentals Of Machine Learning For Predictive Data Analytics

Fundamentals of Machine Learning for Predictive Data Analytics PDF
Author: John D. Kelleher
Publisher: MIT Press
ISBN: 0262331748
Size: 47.91 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 624
View: 6408
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Fundamentals Of Machine Learning For Predictive Data Analytics

by John D. Kelleher, Fundamentals Of Machine Learning For Predictive Data Analytics Books available in PDF, EPUB, Mobi Format. Download Fundamentals Of Machine Learning For Predictive Data Analytics books, A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.




Fundamentals Of Machine Learning

Fundamentals of Machine Learning PDF
Author: Thomas Trappenberg
Publisher: Oxford University Press
ISBN: 0192563092
Size: 25.40 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 304
View: 7355
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Fundamentals Of Machine Learning

by Thomas Trappenberg, Fundamentals Of Machine Learning Books available in PDF, EPUB, Mobi Format. Download Fundamentals Of Machine Learning books, Interest in machine learning is exploding worldwide, both in research and for industrial applications. Machine learning is fast becoming a fundamental part of everyday life. This book is a brief introduction to this area - exploring its importance in a range of many disciplines, from science to engineering, and even its broader impact on our society. The book is written in a style that strikes a balance between brevity of explanation, rigorous mathematical argument, and outlines principle ideas. At the same time, it provides a comprehensive overview of a variety of methods and their application within this field. This includes an introduction to Bayesian approaches to modeling, as well as deep learning. Writing small programs to apply machine learning techniques is made easy by high level programming systems, and this book shows examples in Python with the machine learning libraries 'sklearn' and 'Keras'. The first four chapters concentrate on the practical side of applying machine learning techniques. The following four chapters discuss more fundamental concepts that includes their formulation in a probabilistic context. This is followed by two more chapters on advanced models, that of recurrent neural networks and that of reinforcement learning. The book closes with a brief discussion on the impact of machine learning and AI on our society. Fundamentals of Machine Learning provides a brief and accessible introduction to this rapidly growing field, one that will appeal to students and researchers across computer science and computational neuroscience, as well as the broader cognitive sciences.




Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition

Fundamentals of Machine Learning for Predictive Data Analytics  second edition PDF
Author: John D. Kelleher
Publisher: MIT Press
ISBN: 0262361108
Size: 58.68 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 856
View: 4206
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Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition

by John D. Kelleher, Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition Books available in PDF, EPUB, Mobi Format. Download Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition books, The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.




Fundamentals Of Machine Learning Using Python

Fundamentals of Machine Learning Using Python PDF
Author: Euan Russano
Publisher: Arcler Press
ISBN: 9781774073650
Size: 64.80 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 290
View: 4495
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Fundamentals Of Machine Learning Using Python

by Euan Russano, Fundamentals Of Machine Learning Using Python Books available in PDF, EPUB, Mobi Format. Download Fundamentals Of Machine Learning Using Python books, Fundamentals of Machine Learning discusses the basics of python, use of python in computing and provides a general outlook on machine learning. This book provides an insight into concepts such as linear regression with one variable, linear algebra, and linear regression with multiple inputs. The classification with logistics regression model, regularization, neural networks, decision trees are explained in this book. The introduction to several concepts of machine learning such as component analysis, classification using k-Nearest Algorithm, k Means Clustering, computing with Tensor flow and natural language processing have been explained. This book explains the fundamental concepts of machine learning.




Fundamentals Of Deep Learning

Fundamentals of Deep Learning PDF
Author: Nikhil Buduma
Publisher: "O'Reilly Media, Inc."
ISBN: 1491925566
Size: 75.21 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 298
View: 330
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Fundamentals Of Deep Learning

by Nikhil Buduma, Fundamentals Of Deep Learning Books available in PDF, EPUB, Mobi Format. Download Fundamentals Of Deep Learning books, With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning




Fundamentals Of Pattern Recognition And Machine Learning

Fundamentals of Pattern Recognition and Machine Learning PDF
Author: Ulisses de Mendonça Braga-Neto
Publisher:
ISBN: 3030276562
Size: 21.42 MB
Format: PDF, Docs
Category : Electronic books
Languages : en
Pages :
View: 289
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Fundamentals Of Pattern Recognition And Machine Learning

by Ulisses de Mendonça Braga-Neto, Fundamentals Of Pattern Recognition And Machine Learning Books available in PDF, EPUB, Mobi Format. Download Fundamentals Of Pattern Recognition And Machine Learning books, Fundamentals of Pattern Recognition and Machine Learning is designed for a one or two-semester introductory course in Pattern Recognition or Machine Learning at the graduate or advanced undergraduate level. The book combines theory and practice and is suitable to the classroom and self-study. The book is intended to be concise but thorough. It does not attempt an encyclopedic approach, but covers in significant detail the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as Gaussian process regression and convolutional neural networks. In addition, the selection of topics has a few features that are unique among comparable texts: it contains an extensive chapter on classifier error estimation, as well as sections on Bayesian classification, Bayesian error estimation, separate sampling, and rank-based classification. The book is mathematically rigorous and covers the classical theorems in the area. Nevertheless, an effort is made in the book to strike a balance between theory and practice. In particular, examples with datasets from applications in bioinformatics and materials informatics are used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and scikit-learn. All plots in the text were generated using python scripts, which are also available on the book website.




Einf Hrung In Machine Learning Mit Python

Einf  hrung in Machine Learning mit Python PDF
Author: Andreas C. Müller
Publisher: O'Reilly
ISBN: 3960101120
Size: 60.14 MB
Format: PDF
Category : Computers
Languages : de
Pages : 378
View: 3242
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Einf Hrung In Machine Learning Mit Python

by Andreas C. Müller, Einf Hrung In Machine Learning Mit Python Books available in PDF, EPUB, Mobi Format. Download Einf Hrung In Machine Learning Mit Python books, Machine Learning ist zu einem wichtigen Bestandteil vieler kommerzieller Anwendungen und Forschungsprojekte geworden, von der medizinischen Diagnostik bis hin zur Suche nach Freunden in sozialen Netzwerken. Um Machine-Learning-Anwendungen zu entwickeln, braucht es keine großen Expertenteams: Wenn Sie Python-Grundkenntnisse mitbringen, zeigt Ihnen dieses Praxisbuch, wie Sie Ihre eigenen Machine-Learning-Lösungen erstellen. Mit Python und der scikit-learn-Bibliothek erarbeiten Sie sich alle Schritte, die für eine erfolgreiche Machine-Learning-Anwendung notwendig sind. Die Autoren Andreas Müller und Sarah Guido konzentrieren sich bei der Verwendung von Machine-Learning-Algorithmen auf die praktischen Aspekte statt auf die Mathematik dahinter. Wenn Sie zusätzlich mit den Bibliotheken NumPy und matplotlib vertraut sind, hilft Ihnen dies, noch mehr aus diesem Tutorial herauszuholen. Das Buch zeigt Ihnen: - grundlegende Konzepte und Anwendungen von Machine Learning - Vor- und Nachteile weit verbreiteter maschineller Lernalgorithmen - wie sich die von Machine Learning verarbeiteten Daten repräsentieren lassen und auf welche Aspekte der Daten Sie sich konzentrieren sollten - fortgeschrittene Methoden zur Auswertung von Modellen und zum Optimieren von Parametern - das Konzept von Pipelines, mit denen Modelle verkettet und Arbeitsabläufe gekapselt werden - Arbeitsmethoden für Textdaten, insbesondere textspezifische Verarbeitungstechniken - Möglichkeiten zur Verbesserung Ihrer Fähigkeiten in den Bereichen Machine Learning und Data Science Dieses Buch ist eine fantastische, super praktische Informationsquelle für jeden, der mit Machine Learning in Python starten möchte – ich wünschte nur, es hätte schon existiert, als ich mit scikit-learn anfing! Hanna Wallach, Senior Researcher, Microsoft Research




Maschinelles Lernen

Maschinelles Lernen PDF
Author: Jörg Frochte
Publisher: Carl Hanser Verlag GmbH Co KG
ISBN: 3446459979
Size: 42.19 MB
Format: PDF
Category : Technology & Engineering
Languages : de
Pages : 406
View: 4626
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Maschinelles Lernen

by Jörg Frochte, Maschinelles Lernen Books available in PDF, EPUB, Mobi Format. Download Maschinelles Lernen books, Maschinelles Lernen ist ein interdisziplinäres Fach, das die Bereiche Informatik, Mathematik und das jeweilige Anwendungsgebiet zusammenführt. In diesem Buch werden alle drei Teilgebiete gleichermaßen berücksichtigt: - Es wird demonstriert, wie man die Algorithmen des maschinellen Lernens verwendet und der Hintergrund geliefert, um zu verstehen, wie und warum diese Algorithmen funktionieren. - Ebenfalls enthalten ist ein kompakter Kickstart zur Verwendung von Python 3 und seinem Ökosystem im Umfeld des maschinellen Lernens. - Die Algorithmen werden zum besseren Verständnis und praktischen Einsatz anschaulich mittels NumPy und SciPy umgesetzt. - Für die Support Vector Machines und das Deep Learning wird auf scikit-learn bzw. Keras zurückgegriffen. - Es werden verschiedene Methoden des überwachten, unüberwachten und bestärkenden Lernens besprochen, u.a. Random Forest, DBSCAN und Q-Learning. Vorausgesetzt werden Kenntnisse in objektorientierter Programmierung und Basiswissen der Hochschulmathematik. Die nötige Mathematik wird eingebettet im Buch präsentiert und die Theorie direkt in Python-Code umgesetzt. Das Buch ist ideal für Studierende der Informatik, Mechatronik, Elektrotechnik und der angewandten Statistik/Data Science sowie für Ingenieure und Informatiker in der Praxis.




Fundamentals Of Data Analytics

Fundamentals of Data Analytics PDF
Author: Rudolf Mathar
Publisher: Springer Nature
ISBN: 3030568318
Size: 68.91 MB
Format: PDF, Docs
Category : Artificial intelligence
Languages : en
Pages : 127
View: 2034
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Fundamentals Of Data Analytics

by Rudolf Mathar, Fundamentals Of Data Analytics Books available in PDF, EPUB, Mobi Format. Download Fundamentals Of Data Analytics books, This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.