Download or read book Machine Learning Mastery With Weka written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2016-06-23 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is not just for professors. Weka is a top machine learning platform that provides an easy-to-use graphical interface and state-of-the-art algorithms. In this Ebook, learn exactly how to get started with applied machine learning using the Weka platform.
Download or read book Data Mining written by Ian H. Witten and published by Elsevier. This book was released on 2011-02-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
Download or read book Better Deep Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-12-13 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning neural networks have become easy to define and fit, but are still hard to configure. Discover exactly how to improve the performance of deep learning neural network models on your predictive modeling projects. With clear explanations, standard Python libraries, and step-by-step tutorial lessons, you’ll discover how to better train your models, reduce overfitting, and make more accurate predictions.
Download or read book Master Machine Learning Algorithms written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2016-03-04 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: You must understand the algorithms to get good (and be recognized as being good) at machine learning. In this Ebook, finally cut through the math and learn exactly how machine learning algorithms work, then implement them from scratch, step-by-step.
Download or read book Data Mining and Data Warehousing written by Parteek Bhatia and published by Cambridge University Press. This book was released on 2019-04-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.
Download or read book Deep Learning With Python written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2016-05-13 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. In this Ebook, learn exactly how to get started and apply deep learning to your own machine learning projects.
Download or read book Machine Learning Mastery With Python written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2016-04-08 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Python ecosystem with scikit-learn and pandas is required for operational machine learning. Python is the rising platform for professional machine learning because you can use the same code to explore different models in R&D then deploy it directly to production. In this Ebook, learn exactly how to get started and apply machine learning using the Python ecosystem.
Download or read book Probability for Machine Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2019-09-24 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability is the bedrock of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in probability that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of probability to machine learning, Bayesian probability, entropy, density estimation, maximum likelihood, and much more.
Download or read book Machine Learning Mastery With R written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2016-01-30 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: R has been the gold standard in applied machine learning for a long time. Surveys show that it is the most popular platform used by professional data scientists. It is also preferred by the best data scientists in the world. In this Ebook, learn how to get started, practice and apply machine learning using the R platform.
Download or read book Machine Learning with the Raspberry Pi written by Donald J. Norris and published by Apress. This book was released on 2019-11-29 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using the Pi Camera and a Raspberry Pi board, expand and replicate interesting machine learning (ML) experiments. This book provides a solid overview of ML and a myriad of underlying topics to further explore. Non-technical discussions temper complex technical explanations to make the hottest and most complex topic in the hobbyist world of computing understandable and approachable. Machine learning, also commonly referred to as deep learning (DL), is currently being integrated into a multitude of commercial products as well as widely being used in industrial, medical, and military applications. It is hard to find any modern human activity, which has not been "touched" by artificial intelligence (AI) applications. Building on the concepts first presented in Beginning Artificial Intelligence with the Raspberry Pi, you’ll go beyond simply understanding the concepts of AI into working with real machine learning experiments and applying practical deep learning concepts to experiments with the Pi board and computer vision. What you learn with Machine Learning with the Raspberry Pi can then be moved on to other platforms to go even further in the world of AI and ML to better your hobbyist or commercial projects. What You'll Learn Acquire a working knowledge of current ML Use the Raspberry Pi to implement ML techniques and algorithms Apply AI and ML tools and techniques to your own work projects and studies Who This Book Is For Engineers and scientists but also experienced makers and hobbyists. Motivated high school students who desire to learn about ML can benefit from this material with determination.
Download or read book Applications of Artificial Intelligence and Machine Learning written by Ankur Choudhary and published by Springer Nature. This book was released on 2021-07-27 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business, and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics, and practitioners in the industry working on AI applications.
Download or read book Machine Learning with Health Care Perspective written by Vishal Jain and published by Springer Nature. This book was released on 2020-03-09 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.
Download or read book Machine Learning with R written by Brett Lantz and published by Packt Publishing Ltd. This book was released on 2013-10-25 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.
Download or read book Natural Language Processing with Python written by Steven Bird and published by "O'Reilly Media, Inc.". This book was released on 2009-06-12 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
Download or read book Feature Engineering for Machine Learning written by Alice Zheng and published by "O'Reilly Media, Inc.". This book was released on 2018-03-23 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering. Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples. You’ll examine: Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms Natural text techniques: bag-of-words, n-grams, and phrase detection Frequency-based filtering and feature scaling for eliminating uninformative features Encoding techniques of categorical variables, including feature hashing and bin-counting Model-based feature engineering with principal component analysis The concept of model stacking, using k-means as a featurization technique Image feature extraction with manual and deep-learning techniques
Download or read book The Art of Feature Engineering written by Pablo Duboue and published by Cambridge University Press. This book was released on 2020-06-25 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide for data scientists who want to improve the performance of any machine learning solution with feature engineering.
Download or read book AI and Machine Learning Paradigms for Health Monitoring System written by Hasmat Malik and published by Springer Nature. This book was released on 2021-02-14 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners.
