Download or read book MATLAB for Machine Learning written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2017-08-28 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extract patterns and knowledge from your data in easy way using MATLAB About This Book Get your first steps into machine learning with the help of this easy-to-follow guide Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn Learn the introductory concepts of machine learning. Discover different ways to transform data using SAS XPORT, import and export tools, Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Download or read book Big Data Analytics written by C. Perez and published by CESAR PEREZ. This book was released on 2020-05-31 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. MATLAB has the tool Neural Network Toolbox (Deep Learning Toolbox from version 18) that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control.The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Big Data tools (Parallel Computing Toolbox). Unsupervised learning algorithms, including self-organizing maps and competitive layers-Apps for data-fitting, pattern recognition, and clustering-Preprocessing, postprocessing, and network visualization for improving training efficiency and assessing network performance. his book develops cluster analysis and pattern recognition

Download or read book Data Clustering Theory Algorithms and Applications Second Edition written by Guojun Gan and published by SIAM. This book was released on 2020-11-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.

Download or read book Machine and Deep Learning Using MATLAB written by Kamal I. M. Al-Malah and published by John Wiley & Sons. This book was released on 2023-10-12 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: MACHINE AND DEEP LEARNING In-depth resource covering machine and deep learning methods using MATLAB tools and algorithms, providing insights and algorithmic decision-making processes Machine and Deep Learning Using MATLAB introduces early career professionals to the power of MATLAB to explore machine and deep learning applications by explaining the relevant MATLAB tool or app and how it is used for a given method or a collection of methods. Its properties, in terms of input and output arguments, are explained, the limitations or applicability is indicated via an accompanied text or a table, and a complete running example is shown with all needed MATLAB command prompt code. The text also presents the results, in the form of figures or tables, in parallel with the given MATLAB code, and the MATLAB written code can be later used as a template for trying to solve new cases or datasets. Throughout, the text features worked examples in each chapter for self-study with an accompanying website providing solutions and coding samples. Highlighted notes draw the attention of the user to critical points or issues. Readers will also find information on: Numeric data acquisition and analysis in the form of applying computational algorithms to predict the numeric data patterns (clustering or unsupervised learning) Relationships between predictors and response variable (supervised), categorically sub-divided into classification (discrete response) and regression (continuous response) Image acquisition and analysis in the form of applying one of neural networks, and estimating net accuracy, net loss, and/or RMSE for the successive training, validation, and testing steps Retraining and creation for image labeling, object identification, regression classification, and text recognition Machine and Deep Learning Using MATLAB is a useful and highly comprehensive resource on the subject for professionals, advanced students, and researchers who have some familiarity with MATLAB and are situated in engineering and scientific fields, who wish to gain mastery over the software and its numerous applications.

Download or read book Sea Ice Image Processing with MATLAB written by Qin Zhang and published by CRC Press. This book was released on 2018-02-13 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sea Ice Image Processing with MATLAB addresses the topic of image processing for the extraction of key sea ice characteristics from digital photography, which is of great relevance for Artic remote sensing and marine operations. This valuable guide provides tools for quantifying the ice environment that needs to be identified and reproduced for such testing. This includes fit-for-purpose studies of existing vessels, new-build conceptual design and detailed engineering design studies for new developments, and studies of demanding marine operations involving multiple vessels and operational scenarios in sea ice. A major contribution of this work is the development of automated computer algorithms for efficient image analysis. These are used to process individual sea-ice images and video streams of images to extract parameters such as ice floe size distribution, and ice types. Readers are supplied with Matlab source codes of the algorithms for the image processing methods discussed in the book made available as online material. Features Presents the first systematic work using image processing techniques to identify ice floe size distribution from aerial images Helps identify individual ice floe and obtain floe size distributions for Arctic offshore operations and transportation Explains specific algorithms that can be combined to solve various problems during polar sea ice investigations Includes MATLAB® codes useful not only for academics, but for ice engineers and scientists to develop tools applicable in different areas such as sustainable arctic marine and coastal technology research Provides image processing techniques applicable to other fields like biomedicine, material science, etc

Download or read book Exploratory Data Analysis with MATLAB written by Wendy L. Martinez and published by CRC Press. This book was released on 2017-08-07 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data

Download or read book Classification and Clustering in Biomedical Signal Processing written by Dey, Nilanjan and published by IGI Global. This book was released on 2016-04-07 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research findings in the areas of signal processing for biomedical applications with an emphasis on classification and clustering techniques, this essential publication is designed for use by medical professionals, IT developers, and advanced-level graduate students.

Download or read book Big Data Analytics written by C. Perez and published by CESAR PEREZ. This book was released on 2020-05-31 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data analytics is the process of collecting, organizing and analyzing large sets of data (called big data) to discover patterns and other useful information. Big data analytics can help organizations to better understand the information contained within the data and will also help identify the data that is most important to the business and future business decisions. Analysts working with big data basically want the knowledge that comes from analyzing the data.To analyze such a large volume of data, big data analytics is typically performed using specialized software tools and applications for predictive analytics, data mining, text mining, forecasting and data optimization. Collectively these processes are separate but highly integrated functions of high-performance analytics. Using big data tools and software enables an organization to process extremely large volumes of data that a business has collected to determine which data is relevant and can be analyzed to drive better business decisions in the future. Among all these tools highlights MATLAB. MATLAB implements various toolboxes for working on big data analytics, such as Statistics Toolbox and Neural Network Toolbox (Deep Learning Toolbox for version 18) . This book develops the work capabilities of MATLAB with Neural Networks and Big Data.

Download or read book Integrative Cluster Analysis in Bioinformatics written by Basel Abu-Jamous and published by John Wiley & Sons. This book was released on 2015-04-16 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review of clustering analysis in bioinformatics from the fundamentals through to state-of-the-art techniques and applications. Key Features: Offers a contemporary review of clustering methods and applications in the field of bioinformatics, with particular emphasis on gene expression analysis Provides an excellent introduction to molecular biology with computer scientists and information engineering researchers in mind, laying out the basic biological knowledge behind the application of clustering analysis techniques in bioinformatics Explains the structure and properties of many types of high-throughput datasets commonly found in biological studies Discusses how clustering methods and their possible successors would be used to enhance the pace of biological discoveries in the future Includes a companion website hosting a selected collection of codes and links to publicly available datasets

Download or read book Intelligent Multidimensional Data Clustering and Analysis written by Bhattacharyya, Siddhartha and published by IGI Global. This book was released on 2016-11-29 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining analysis techniques have undergone significant developments in recent years. This has led to improved uses throughout numerous functions and applications. Intelligent Multidimensional Data Clustering and Analysis is an authoritative reference source for the latest scholarly research on the advantages and challenges presented by the use of cluster analysis techniques. Highlighting theoretical foundations, computing paradigms, and real-world applications, this book is ideally designed for researchers, practitioners, upper-level students, and professionals interested in the latest developments in cluster analysis for large data sets.

Download or read book Computing Control Information and Education Engineering written by Hsiang-Chuan Liu and published by CRC Press. This book was released on 2015-08-18 with total page 1038 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings set contains selected Computer, Information and Education Technology related papers from the 2015 International Conference on Computer, Intelligent Computing and Education Technology (CICET 2015), to be held April 11-12, 2015 in Guilin, P.R. China. The proceedings aims to provide a platform for researchers, engineers and academics

Download or read book Clustering Algorithms written by John A. Hartigan and published by John Wiley & Sons. This book was released on 1975 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shows how Galileo, Newton, and Einstein tried to explain gravity. Discusses the concept of microgravity and NASA's research on gravity and microgravity.

Download or read book Intelligent Information Processing with Matlab written by Xiu Zhang and published by Springer Nature. This book was released on 2023-10-15 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive collection of technologies and methods on intelligent information processing, which includes artificial neural network, fuzzy logic, and evolutionary computing. It also introduces the latest research directions and progress in intelligent information processing, such as transfer learning through convolutional neural network, time series prediction, clustering based on fuzzy neural network, test and evaluation of the traveling salesman problem, test and evaluation of continuous optimization problem, and more. This book promotes the development and application of intelligent information processing technology in the field of computational intelligence, effectively improving the intersection and integration of intelligent information processing methods. Researchers in computational intelligence and artificial intelligence technology, as well as teachers, students, and others interested in the subject, will benefit from this book.

Download or read book Communication Signal Processing Information Technology written by Faouzi Derbel and published by Walter de Gruyter GmbH & Co KG. This book was released on 2017-03-20 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Communication & Signal Processing involving topics such as: Communications Theory and Techniques, Communications Protocols and Standards, Telecommunication Systems, Modulation and Signal Design, Coding Compression and Information Theory, Communication Networks, Wireless Communication, Optical Communication, Wireless Sensor Networks, MIMO Systems, MIMO Communications, Signal Processing for Communications e-Learning. Digital Signal Processing, Multiresolution Analysis, Wavelets, Smart Antennas, Adaptive Antennas, Theory and Practice of Signal Processing, Digital Signal Processing, Speech, Image, Video Signal Processing, Person Authentication, Biometry, Medical Imaging, Remote Sensing Analysis, Image Indexation, Image compression, Data Fusion and Pattern Recognition, Parallel Computing, Artificial Intelligence, Information Retrieval.

Download or read book The Alzheimer s Disease Challenge written by Athanasios Alexiou and published by Frontiers Media SA. This book was released on 2019-12-04 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Alzheimer’s disease is undoubtedly the major health challenge of our Century with significant social and economic consequences. This Frontiers eBook offers a contribution of 39 innovative papers on the multidimensional and crucial problem of Alzheimer’s disease management and treatment. Several perspectives, research updates, and trials describing methods on potential diagnosis and treatment are presented including biological mechanisms, biomarkers and risk factors for an early and efficient prognosis, diagnosis and prevention. Additionally, while the rapidly increasing Alzheimer’s disease population demands holistic solutions and clinical studies with new therapeutic target approaches, several of the contributive papers present promising drugs targeting Alzheimer’s disease treatment. We give our deepest acknowledgment to all the authors for their important and innovative contributions, to the reviewers for their valuable recommendations on improving the submitting studies and all the Frontiers Editorial team for continuous support.

Download or read book Sustainable Development Goal 14 Life Below Water Towards a Sustainable Ocean written by Emanuele Di Lorenzo and published by Frontiers Media SA. This book was released on 2022-03-15 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Gmdh methodology And Implementation In Matlab written by Godfrey C Onwubolu and published by World Scientific. This book was released on 2016-06-14 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Group method of data handling (GMDH) is a typical inductive modeling method built on the principles of self-organization. Since its introduction, inductive modelling has been developed to support complex systems in prediction, clusterization, system identification, as well as data mining and knowledge extraction technologies in social science, science, engineering, and medicine.This is the first book to explore GMDH using MATLAB (matrix laboratory) language. Readers will learn how to implement GMDH in MATLAB as a method of dealing with big data analytics. Error-free source codes in MATLAB have been included in supplementary material (accessible online) to assist users in their understanding in GMDH and to make it easy for users to further develop variations of GMDH algorithms.