Flood Forecasting Using Artificial Neural Networks

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Flood Forecasting Using Machine Learning Methods

Author : Fi-John Chang
Publisher : MDPI
ISBN 13 : 3038975486
Total Pages : 376 pages
Book Rating : 4.0/5 (389 download)

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Book Synopsis Flood Forecasting Using Machine Learning Methods by : Fi-John Chang

Download or read book Flood Forecasting Using Machine Learning Methods written by Fi-John Chang and published by MDPI. This book was released on 2019-02-28 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, the degree and scale of flood hazards has been massively increasing as a result of the changing climate, and large-scale floods jeopardize lives and properties, causing great economic losses, in the inundation-prone areas of the world. Early flood warning systems are promising countermeasures against flood hazards and losses. A collaborative assessment according to multiple disciplines, comprising hydrology, remote sensing, and meteorology, of the magnitude and impacts of flood hazards on inundation areas significantly contributes to model the integrity and precision of flood forecasting. Methodologically oriented countermeasures against flood hazards may involve the forecasting of reservoir inflows, river flows, tropical cyclone tracks, and flooding at different lead times and/or scales. Analyses of impacts, risks, uncertainty, resilience, and scenarios coupled with policy-oriented suggestions will give information for flood hazard mitigation. Emerging advances in computing technologies coupled with big-data mining have boosted data-driven applications, among which Machine Learning technology, with its flexibility and scalability in pattern extraction, has modernized not only scientific thinking but also predictive applications. This book explores recent Machine Learning advances on flood forecast and management in a timely manner and presents interdisciplinary approaches to modelling the complexity of flood hazards-related issues, with contributions to integrative solutions from a local, regional or global perspective.

Flood Forecasting Using Artificial Neural Networks

Author : P Varoonchotikul
Publisher : CRC Press
ISBN 13 : 9789058096319
Total Pages : 102 pages
Book Rating : 4.0/5 (963 download)

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Book Synopsis Flood Forecasting Using Artificial Neural Networks by : P Varoonchotikul

Download or read book Flood Forecasting Using Artificial Neural Networks written by P Varoonchotikul and published by CRC Press. This book was released on 2003-01-01 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Flood disasters continue to occur in many countries in the world and cause tremendous casualties and property damage. To mitigate the effects of floods, a range of structural and non-structural measures have been employed including dykes, channelling, flood-proofing property, land-use regulation and flood warning schemes. Such schemes can include the use of Artificial Neural Networks (ANN) for modelling the rainfall run-off process as it is a quick and flexible approach which gives very promising results. However, the inability of ANN to extrapolate beyond the limits of the training range is a serious limitation of the method, and this book examines ways of side-stepping or solving this complex issue.

Spatial Modeling in GIS and R for Earth and Environmental Sciences

Author : Hamid Reza Pourghasemi
Publisher : Elsevier
ISBN 13 : 0128156953
Total Pages : 800 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Spatial Modeling in GIS and R for Earth and Environmental Sciences by : Hamid Reza Pourghasemi

Download or read book Spatial Modeling in GIS and R for Earth and Environmental Sciences written by Hamid Reza Pourghasemi and published by Elsevier. This book was released on 2019-01-18 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. - Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography - Provides an overview, methods and case studies for each application - Expresses concepts and methods at an appropriate level for both students and new users to learn by example

Flood Forecasting Using Artificial Neural Networks

Author : P. Varoonchotikul
Publisher : CRC Press
ISBN 13 : 9781138475076
Total Pages : pages
Book Rating : 4.4/5 (75 download)

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Book Synopsis Flood Forecasting Using Artificial Neural Networks by : P. Varoonchotikul

Download or read book Flood Forecasting Using Artificial Neural Networks written by P. Varoonchotikul and published by CRC Press. This book was released on 2017-10-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation considers various questions with respect to the effects of salinity on nutrification: what are the main inhibiting factors causing the effects, do all salts have similar effects, what is the maximum acceptable salt level, are ammonia oxidisers or nitrite oxidizers most sensitive to salt stress, can nitrifiers adapt to long term salt stress and are some specific nitrifiers more resistant to salt stress than others? Research was carried out at laboratory scale and in full-scale plants and modelling was employed in both phases to provide a mathematical description for salt inhibition on nitrification and to facilitate the comparison. The result has led to an improved understanding of the effect of salinity on nitrification. The results can be used to improve the sustainability of the exisisting wastewater treatment plants operated under salt stress.

Geospatial Technologies for Land and Water Resources Management

Author : Ashish Pandey
Publisher : Springer Nature
ISBN 13 : 3030904792
Total Pages : 617 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Geospatial Technologies for Land and Water Resources Management by : Ashish Pandey

Download or read book Geospatial Technologies for Land and Water Resources Management written by Ashish Pandey and published by Springer Nature. This book was released on 2021-12-06 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the application of geospatial technologies to study the land use land cover (LULC) dynamics, agricultural water management, water resources assessment and modeling, and studies on natural disasters. LULC dynamics is one of the major research themes for studying global environmental change using remote sensing data. The section on LULC dynamics covers the multi-variate criteria for land use and land cover classification and change assessment in the mountainous regions. Further, LULC change detection of the Tons river basin and LULC dynamics at decadal frequency are studied to derive adaptation and mitigation strategies. Landscape-level forest disturbance modeling, together with conservation implications, is also included. The watershed management approach is necessary for comprehensive management of land and water resources of any region, where studies on multi-criteria analysis for rainwater harvesting planning and its impact on land use land cover transformations in rain-fed areas using geospatial technologies are presented in this book. The book will be useful for academics, water practitioners, scientists, water managers, environmentalists, and administrators, NGOs, researchers, and students who are actively involved in the application of geospatial technologies in LULC studies, agricultural water management and hydrological modelling and natural disasters for addressing the challenges being posed by climate change while addressing issues of food and water securities

Artificial Neural Networks in Hydrology

Author : R.S. Govindaraju
Publisher : Springer Science & Business Media
ISBN 13 : 9401593418
Total Pages : 338 pages
Book Rating : 4.4/5 (15 download)

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Book Synopsis Artificial Neural Networks in Hydrology by : R.S. Govindaraju

Download or read book Artificial Neural Networks in Hydrology written by R.S. Govindaraju and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.

Research Anthology on Artificial Neural Network Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1668424096
Total Pages : 1575 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Research Anthology on Artificial Neural Network Applications by : Management Association, Information Resources

Download or read book Research Anthology on Artificial Neural Network Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-07-16 with total page 1575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.

Recent Trends in Civil Engineering

Author : K. K. Pathak
Publisher : Springer Nature
ISBN 13 : 9811551952
Total Pages : 1081 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Recent Trends in Civil Engineering by : K. K. Pathak

Download or read book Recent Trends in Civil Engineering written by K. K. Pathak and published by Springer Nature. This book was released on 2020-09-27 with total page 1081 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the selected peer-reviewed proceedings of the International Conference on Recent Trends and Innovations in Civil Engineering (ICRTICE 2019). The volume focuses on latest research and advances in the field of civil engineering and materials science such as design and development of new environmental materials, performance testing and verification of smart materials, performance analysis and simulation of steel structures, design and performance optimization of concrete structures, and building materials analysis. The book also covers studies in geotechnical engineering, hydraulic engineering, road and bridge engineering, building services design, engineering management, water resource engineering and renewable energy. The contents of this book will be useful for students, researchers and professionals working in civil engineering.

Fuzzy Systems

Author : Hung T. Nguyen
Publisher : Springer Science & Business Media
ISBN 13 : 1461555051
Total Pages : 532 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Fuzzy Systems by : Hung T. Nguyen

Download or read book Fuzzy Systems written by Hung T. Nguyen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis and control of complex systems have been the main motivation for the emergence of fuzzy set theory since its inception. It is also a major research field where many applications, especially industrial ones, have made fuzzy logic famous. This unique handbook is devoted to an extensive, organized, and up-to-date presentation of fuzzy systems engineering methods. The book includes detailed material and extensive bibliographies, written by leading experts in the field, on topics such as: Use of fuzzy logic in various control systems. Fuzzy rule-based modeling and its universal approximation properties. Learning and tuning techniques for fuzzy models, using neural networks and genetic algorithms. Fuzzy control methods, including issues such as stability analysis and design techniques, as well as the relationship with traditional linear control. Fuzzy sets relation to the study of chaotic systems, and the fuzzy extension of set-valued approaches to systems modeling through the use of differential inclusions. Fuzzy Systems: Modeling and Control is part of The Handbooks of Fuzzy Sets Series. The series provides a complete picture of contemporary fuzzy set theory and its applications. This volume is a key reference for systems engineers and scientists seeking a guide to the vast amount of literature in fuzzy logic modeling and control.

The Application of Neural Networks in the Earth System Sciences

Author : Vladimir M. Krasnopolsky
Publisher : Springer Science & Business Media
ISBN 13 : 9400760736
Total Pages : 205 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis The Application of Neural Networks in the Earth System Sciences by : Vladimir M. Krasnopolsky

Download or read book The Application of Neural Networks in the Earth System Sciences written by Vladimir M. Krasnopolsky and published by Springer Science & Business Media. This book was released on 2013-06-14 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a representative set of Earth System Science (ESS) applications of the neural network (NN) technique. It examines a progression of atmospheric and oceanic problems, which, from the mathematical point of view, can be formulated as complex, multidimensional, and nonlinear mappings. It is shown that these problems can be solved utilizing a particular type of NN – the multilayer perceptron (MLP). This type of NN applications covers the majority of NN applications developed in ESSs such as meteorology, oceanography, atmospheric and oceanic satellite remote sensing, numerical weather prediction, and climate studies. The major properties of the mappings and MLP NNs are formulated and discussed. Also, the book presents basic background for each introduced application and provides an extensive set of references. “This is an excellent book to learn how to apply artificial neural network methods to earth system sciences. The author, Dr. Vladimir Krasnopolsky, is a universally recognized master in this field. With his vast knowledge and experience, he carefully guides the reader through a broad variety of problems found in the earth system sciences where neural network methods can be applied fruitfully. (...) The broad range of topics covered in this book ensures that researchers/graduate students from many fields (...) will find it an invaluable guide to neural network methods.” (Prof. William W. Hsieh, University of British Columbia, Vancouver, Canada) “Vladimir Krasnopolsky has been the “founding father” of applying computation intelligence methods to environmental science; (...) Dr. Krasnopolsky has created a masterful exposition of a young, yet maturing field that promises to advance a deeper understanding of best modeling practices in environmental science.” (Dr. Sue Ellen Haupt, National Center for Atmospheric Research, Boulder, USA) “Vladimir Krasnopolsky has written an important and wonderful book on applications of neural networks to replace complex and expensive computational algorithms within Earth System Science models. He is uniquely qualified to write this book, since he has been a true pioneer with regard to many of these applications. (...) Many other examples of creative emulations will inspire not just readers interested in the Earth Sciences, but any other modeling practitioner (...) to address both theoretical and practical complex problems that may (or will!) arise in a complex system." ” (Prof. Eugenia Kalnay, University of Maryland, USA)

Proceedings of Second Doctoral Symposium on Computational Intelligence

Author : Deepak Gupta
Publisher : Springer Nature
ISBN 13 : 9811633460
Total Pages : 902 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Proceedings of Second Doctoral Symposium on Computational Intelligence by : Deepak Gupta

Download or read book Proceedings of Second Doctoral Symposium on Computational Intelligence written by Deepak Gupta and published by Springer Nature. This book was released on 2021-09-19 with total page 902 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features high-quality research papers presented at Second Doctoral Symposium on Computational Intelligence (DoSCI-2021), organized by Institute of Engineering and Technology (IET), AKTU, Lucknow, India, on 6 March 2021. This book discusses the topics such as computational intelligence, artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum-inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high-performance computing, biomedical computing, decision support and decision making.

IT Convergence and Security 2017

Author : Kuinam J. Kim
Publisher : Springer
ISBN 13 : 9811064512
Total Pages : 361 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis IT Convergence and Security 2017 by : Kuinam J. Kim

Download or read book IT Convergence and Security 2017 written by Kuinam J. Kim and published by Springer. This book was released on 2017-08-28 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first volume of proceedings including selected papers from the International Conference on IT Convergence and Security (ICITCS) 2017, presenting a snapshot of the latest issues encountered in this field. It explores how IT convergence and security issues are core to most current research, and industrial and commercial activities. It consists of contributions covering topics such as machine learning & deep learning, communication and signal processing, computer vision and applications, future network technology, artificial intelligence and robotics. ICITCS 2017 is the latest in a series of highly successful International Conferences on IT Convergence and Security, previously held in Prague, Czech Republic(2016), Kuala Lumpur, Malaysia (2015) Beijing, China (2014), Macau, China (2013), Pyeong Chang, Korea (2012), and Suwon, Korea (2011).

Neural Networks for Hydrological Modeling

Author : Robert Abrahart
Publisher : CRC Press
ISBN 13 : 1135291004
Total Pages : 324 pages
Book Rating : 4.1/5 (352 download)

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Book Synopsis Neural Networks for Hydrological Modeling by : Robert Abrahart

Download or read book Neural Networks for Hydrological Modeling written by Robert Abrahart and published by CRC Press. This book was released on 2004-05-15 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new approach to the fast-developing world of neural hydrological modelling, this book is essential reading for academics and researchers in the fields of water sciences, civil engineering, hydrology and physical geography. Each chapter has been written by one or more eminent experts working in various fields of hydrological modelling. The b

International Conference on Modeling, Optimization, and Computing (ICMOC 2010)

Author : Swapan Paruya
Publisher : American Inst. of Physics
ISBN 13 : 9780735408548
Total Pages : 0 pages
Book Rating : 4.4/5 (85 download)

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Book Synopsis International Conference on Modeling, Optimization, and Computing (ICMOC 2010) by : Swapan Paruya

Download or read book International Conference on Modeling, Optimization, and Computing (ICMOC 2010) written by Swapan Paruya and published by American Inst. of Physics. This book was released on 2010-12-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The topics of the conference are very timely as the phenomenal advancements of computing facilities have pierced every segment of science, engineering and technology to find solutions of complex problems with ever-increasing accuracy and are helping academicians, scientists, researchers, engineers, software developers, and practitioners achieve significant progress in the solution of previously-unsolved problems. This trend is particularly significant in fluid and thermo-fluid mechanics, energy, software engineering, drug delivery systems, system biology, bioinformatics, etc., where computer-based simulation and optimization (online and offline) have found extensive applications. The primary goal of the conference is to promote the applications of modeling, optimization methods and computing methods in the general area of science and engineering.

Mathematical Models of Small Watershed Hydrology and Applications

Author : Vijay P. Singh
Publisher : Water Resources Publication
ISBN 13 : 9781887201353
Total Pages : 984 pages
Book Rating : 4.2/5 (13 download)

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Book Synopsis Mathematical Models of Small Watershed Hydrology and Applications by : Vijay P. Singh

Download or read book Mathematical Models of Small Watershed Hydrology and Applications written by Vijay P. Singh and published by Water Resources Publication. This book was released on 2002 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive account of some of the most popular models of small watershed hydrology and application ~~ of interest to all hydrologic modelers and model users and a welcome and timely edition to any modeling library

Advances in Streamflow Forecasting

Author : Priyanka Sharma
Publisher : Elsevier
ISBN 13 : 0128209240
Total Pages : 406 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Advances in Streamflow Forecasting by : Priyanka Sharma

Download or read book Advances in Streamflow Forecasting written by Priyanka Sharma and published by Elsevier. This book was released on 2021-06-20 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Streamflow Forecasting: From Traditional to Modern Approaches covers the three major data-driven approaches of streamflow forecasting including traditional approach of statistical and stochastic time-series modelling with their recent developments, stand-alone data-driven approach such as artificial intelligence techniques, and modern hybridized approach where data-driven models are combined with preprocessing methods to improve the forecast accuracy of streamflows and to reduce the forecast uncertainties. This book starts by providing the background information, overview, and advances made in streamflow forecasting. The overview portrays the progress made in the field of streamflow forecasting over the decades. Thereafter, chapters describe theoretical methodology of the different data-driven tools and techniques used for streamflow forecasting along with case studies from different parts of the world. Each chapter provides a flowchart explaining step-by-step methodology followed in applying the data-driven approach in streamflow forecasting. This book addresses challenges in forecasting streamflows by abridging the gaps between theory and practice through amalgamation of theoretical descriptions of the data-driven techniques and systematic demonstration of procedures used in applying the techniques. Language of this book is kept simple to make the readers understand easily about different techniques and make them capable enough to straightforward replicate the approach in other areas of their interest. This book will be vital for hydrologists when optimizing the water resources system, and to mitigate the impact of destructive natural disasters such as floods and droughts by implementing long-term planning (structural and nonstructural measures), and short-term emergency warning. Moreover, this book will guide the readers in choosing an appropriate technique for streamflow forecasting depending upon the given set of conditions. - Contributions from renowned researchers/experts of the subject from all over the world to provide the most authoritative outlook on streamflow forecasting - Provides an excellent overview and advances made in streamflow forecasting over the past more than five decades and covers both traditional and modern data-driven approaches in streamflow forecasting - Includes case studies along with detailed flowcharts demonstrating a systematic application of different data-driven models in streamflow forecasting, which helps understand the step-by-step procedures

Feature Engineering for Machine Learning

Author : Alice Zheng
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491953195
Total Pages : 218 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Feature Engineering for Machine Learning by : Alice Zheng

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