Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key FeaturesBuild state-of-the-art algorithms that can solve your business' problemsLearn how to find hidden patterns in your dataRevise key concepts with hands-on exercises using real-world datasetsBook Description Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection. What you will learnImplement clustering methods such as k-means, agglomerative, and divisiveWrite code in R to analyze market segmentation and consumer behaviorEstimate distribution and probabilities of different outcomesImplement dimension reduction using principal component analysisApply anomaly detection methods to identify fraudDesign algorithms with R and learn how to edit or improve codeWho this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including exponents, square roots, means, and medians.
Spy from Unaula takes us to a small sleepy village of Unaula and shows the simple joys, trials and tribulations of Ramchandra's life. Coming from meager means, Ramchandra overcomes unimaginable odds and his dexterous attitude lets him elevate himself from a lowly life. Having lost his mother early, and father averse to the idea of education, he seeks help from his rebellious brother to be able to pursue his dream of being well educated and a career of an officer in the armed forces. This dream did not come easy as the social obligations and customs of those times compelled him to take drastic decisions to fulfill his dreams. In search of a livelihood and bagful of dreams he travels to the ""City of Dreams"" of his time in search of opportunities that would fulfill his dreams. From the famous Mills of Mumbai to being a cycle rickshaw driver in Agra, he consistently moves slowly and steadily towards his goals without complaining of any hardships he bore. Luck favours the brave, and once opportunity struck he seized the opportunity to train himself in the skills needed to land a government job. Starting from the lowest civilian ranks he moves up with an exciting job in Military Intelligence, eventually becoming a spy. The three wars of 1962 with China and 1965 and 1971 with Pakistan were action packed for Ramchandra. Breaking codes, analyzing information over radio to interrogating the war prisoners and eventually participating in the liberation of Bangladesh in 1971 opens up the secret world of intelligence and spying in those times. From war duties to political unrest and busting espionage rings in the country, Ramchandra never failed to find excitement on his job, while his struggle to ensure that his children found the best education, which he himself struggled to get, never ceased inspite of all odds. This book will appeal to readers with its sharp-drawn perspective of life and the journey of a man with a dream and a lot of action from the secret quarters of covert intelligence agencies.
During the Middle Ages, a thriving center for learning and research was Muslim Spain, where students gathered to consult Arabic manuscripts of earlier scientific works and study with famous teachers. One of these teachers was Sa'id al-Andalusi, who in 1068 wrote Kitab Tabaqat al-'Umam, or "Book of the Categories of Nations," which recorded the contributions to science of all known nations. Today, it is one of few surviving medieval Spanish Muslim texts, and this is its first English translation. Science ('ulum), as used by Sa'id and other scholars of that period, is a broad term covering virtually all aspects of human knowledge. After initial discussions of the categories of nations that did or did not cultivate science, Sa'id details the specific contribution of nine nations or peoples-India, Persia, Chaldea, Greece, Rome, Egypt, the Arab Orient, al-Andalus, and the Hebrews. He includes the names of many individual scientists and scholars and describes their various contributions to knowledge, making his book a significant work of reference as well as history.
Over the past several years, extensive research has been done on the microbial production of polyunsaturated fatty acids (PUFA). Regardless, research on the oleaginous microalgae used as feedstock for biofuels production and the overall story about the production of nutraceutical fatty acids from oleaginous microalgae has been very limited. This volume provides an exclusive insight on the production of nutraceutical fatty acids from oleaginous microalgae and their role on human health. Some saturated and monounsaturated fatty acids can be synthesized by humans, whereas long-chain polyunsaturated fatty acids (PUFAs) such as α-linolenic acid and linoleic acid cannot and are deemed essential. The products of these acids, such as DHA, which is important for early visual and neurological development, are extremely important to human health. Replacing SFAs with omega-3 and omega-6 fatty acids in the diet reduce the risk of cardiovascular diseases and prevent Alzheimer's, bipolar disorder, and schizophrenia, among other benefits. The ever-rising global demand for omega-3 & 6 PUFAs, however, cannot be met solely by fish oil, due to diminishing fish stocks and pollution of marine ecosystems, which has led to increased interest in alternative sustainable sources. Vegetable oils from genetically engineered plant oilseeds and microorganisms are two potential alternatives to fish oil, even though omega-3 PUFAs are highest in the latter. Although transgenic plants present numerous advantages, their production is dependent on seasonal and climatic conditions and the availability of arable land. Moreover, there are public concerns regarding the cultivation of transgenic crops in open ecosystems. These, together with regulatory issues restrict the large-scale production of genetically modified crops. Microorganisms, however, are known natural producers of microbial oils similar to those obtained from plants and animals and a possible source of nutritionally important omega-3 & 6 PUFAs. This groundbreaking volume presents invaluable new research on essential fatty acids, their production from various oleaginous microorganisms, biochemical and metabolic engineering to improve PUFAs content in oil, extraction and purification of omega 3 fatty acids, and the current market scenario. Whether a veteran engineer or scientist using it as a reference or a professor using it as a textbook, this outstanding new volume is a must-have for any engineer or scientist working in food science.
The first trimester of pregnancy is a period of major development for a foetus. It can also be a dangerous time with the highest risk of miscarriage during the first few months. This book is a comprehensive guide to the first trimester of pregnancy for obstetricians and gynaecologists. Beginning with the basics of physiology, the following chapters describe changes in the body, screening, dietary advice, exercise, travel and the effects of smoking and alcohol. The book covers the management of numerous disorders that may be associated with first trimester pregnancy, including ectopic pregnancy, recurrent miscarriage, breast diseases, sepsis and gynaecological problems. The final chapters examine termination and medicolegal aspects. Key points Guide to first trimester pregnancy for obstetricians and gynaecologists Covers management of numerous associated disorders Includes surgical procedures and anaesthesia during the first trimester Nearly 170 images, illustrations and tables
This book presents an in-depth analysis of key recommendations of the consecutive state finance commissions (SFCs) across states of India in the local and national perspective. It reviews the working of SFCs and their critical role in strengthening local governments, both Panchayats and municipalities in the various states. The volume attempts to identify some of the emerging issues related to the efficacy of SFC in fiscal decentralization. It appraises nearly eighty SFC reports and actions taken thereon by the respective State Governments with contextual analysis.
EEG Brain Signal Classification for Epileptic Seizure Disorder Detection provides the knowledge necessary to classify EEG brain signals to detect epileptic seizures using machine learning techniques. Chapters present an overview of machine learning techniques and the tools available, discuss previous studies, present empirical studies on the performance of the NN and SVM classifiers, discuss RBF neural networks trained with an improved PSO algorithm for epilepsy identification, and cover ABC algorithm optimized RBFNN for classification of EEG signal. Final chapter present future developments in the field. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need the most recent and promising automated techniques for EEG classification. - Explores machine learning techniques that have been modified and validated for the purpose of EEG signal classification using Discrete Wavelet Transform for the identification of epileptic seizures - Encompasses machine learning techniques, providing an easily understood resource for both non-specialized readers and biomedical researchers - Provides a number of experimental analyses, with their results discussed and appropriately validated
In a world of shadows and secrets, Cyrus Engineer, an unassuming Parsi, is thrust into the highest office of India. As he grapples with unexpected power dynamics, old allegiances, and emerging conspiracies, one question looms large: Who truly holds the power in this new Bharat? When the fate of a newly born nation transforms into a high-stakes game on a grand chessboard, every move is laced with suspense and mystery. Unexpected allies, hidden motives, and international machinations converge in this intricate thriller. In the sprawling labyrinth of New Bharat’s politics, can Prime Minister Cyrus discern friend from foe? Dive into the Chronicles of New Bharat and uncover the enigma. The board is set, the pieces are moving. Who will claim victory in this riveting game of strategy and subterfuge?
The Magnesium Technology Symposium, the event on which this collection is based, is one of the largest yearly gatherings of magnesium specialists in the world. Papers represent all aspects of the field, ranging from primary production to applications to recycling. Moreover, papers explore everything from basic research findings to industrialization. Magnesium Technology 2015 covers a broad spectrum of current topics, including alloys and their properties; cast products and processing; wrought products and processing; forming, joining, and machining; corrosion and surface finishing; ecology; and structural applications. In addition, there is coverage of new and emerging applications. The collection includes more than 80 papers.
Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key FeaturesBuild state-of-the-art algorithms that can solve your business' problemsLearn how to find hidden patterns in your dataRevise key concepts with hands-on exercises using real-world datasetsBook Description Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection. What you will learnImplement clustering methods such as k-means, agglomerative, and divisiveWrite code in R to analyze market segmentation and consumer behaviorEstimate distribution and probabilities of different outcomesImplement dimension reduction using principal component analysisApply anomaly detection methods to identify fraudDesign algorithms with R and learn how to edit or improve codeWho this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including exponents, square roots, means, and medians.
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