An Introduction to Machine Learning


Book Description

Just like electricity, Machine Learning will revolutionize our life in many ways – some of which are not even conceivable today. This book provides a thorough conceptual understanding of Machine Learning techniques and algorithms. Many of the mathematical concepts are explained in an intuitive manner. The book starts with an overview of machine learning and the underlying Mathematical and Statistical concepts before moving onto machine learning topics. It gradually builds up the depth, covering many of the present day machine learning algorithms, ending in Deep Learning and Reinforcement Learning algorithms. The book also covers some of the popular Machine Learning applications. The material in this book is agnostic to any specific programming language or hardware so that readers can try these concepts on whichever platforms they are already familiar with. Offers a comprehensive introduction to Machine Learning, while not assuming any prior knowledge of the topic; Provides a complete overview of available techniques and algorithms in conceptual terms, covering various application domains of machine learning; Not tied to any specific software language or hardware implementation.




Clouds and Climate


Book Description

"Clouds have always fascinated humans, but never has the need to understand them been so vital. As global surface temperature increases, human activities influence particulate matter in the atmosphere, and the properties of the land surface, clouds are expected to change, with manifold consequences for the climate. Clouds influence climate through their regulation of radiant energy transfer, through their role in convective energy transport, and in mediating the water cycle. Cloud research has never been so exciting. It is a topic with many new opportunities. New satellite observations from space with active instruments such as lidar and radar allow for the first time to reconstruct the three-dimensional distribution of clouds across Earth. Likewise, numerical simulations are beginning to globally resolve the three spatial dimensions of clouds as well as their dynamic evolution. This is enabling researchers, for the first time, to link the smallscale cloud processes and the basic laws that govern them to the general circulation of the atmosphere. These new types of observations, and simulation, are enabling researchers to distinguish how different cloud types influence the climate, and are guiding conceptual representations of their collective behaviour"--




Artificial Intelligence Methods in the Environmental Sciences


Book Description

How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.







Introduction to Deep Learning


Book Description

A project-based guide to the basics of deep learning. This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning. The author, a longtime artificial intelligence researcher specializing in natural-language processing, covers feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and other fundamental concepts and techniques. Students and practitioners learn the basics of deep learning by working through programs in Tensorflow, an open-source machine learning framework. “I find I learn computer science material best by sitting down and writing programs,” the author writes, and the book reflects this approach. Each chapter includes a programming project, exercises, and references for further reading. An early chapter is devoted to Tensorflow and its interface with Python, the widely used programming language. Familiarity with linear algebra, multivariate calculus, and probability and statistics is required, as is a rudimentary knowledge of programming in Python. The book can be used in both undergraduate and graduate courses; practitioners will find it an essential reference.




Free Space Optical Communication


Book Description

This book provides an in-depth understanding of free space optical (FSO) communication with a particular emphasis on optical beam propagation through atmospheric turbulence. The book is structured in such a way that it provides a basic framework for the beginners and also gives a concise description from a designer’s perspective. The book provides an exposure to FSO technology, fundamental limitations, design methodologies, system trade-offs, acquisition, tracking and pointing (ATP) techniques and link-feasibility analysis. The contents of this book will be of interest to professionals and researchers alike. The book may also be used as a textbook for engineering coursework and professional training.




Springer Handbook of Acoustics


Book Description

This is an unparalleled modern handbook reflecting the richly interdisciplinary nature of acoustics edited by an acknowledged master in the field. The handbook reviews the most important areas of the subject, with emphasis on current research. The authors of the various chapters are all experts in their fields. Each chapter is richly illustrated with figures and tables. The latest research and applications are incorporated throughout, including computer recognition and synthesis of speech, physiological acoustics, diagnostic imaging and therapeutic applications and acoustical oceanography. An accompanying CD-ROM contains audio and video files.




Aviation Turbulence


Book Description

Anyone who has experienced turbulence in flight knows that it is usually not pleasant, and may wonder why this is so difficult to avoid. The book includes papers by various aviation turbulence researchers and provides background into the nature and causes of atmospheric turbulence that affect aircraft motion, and contains surveys of the latest techniques for remote and in situ sensing and forecasting of the turbulence phenomenon. It provides updates on the state-of-the-art research since earlier studies in the 1960s on clear-air turbulence, explains recent new understanding into turbulence generation by thunderstorms, and summarizes future challenges in turbulence prediction and avoidance.




MATLAB Machine Learning


Book Description

This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews commercially available packages for machine learning and shows how they fit into the field. The book then shows how MATLAB can be used to solve machine learning problems and how MATLAB graphics can enhance the programmer’s understanding of the results and help users of their software grasp the results. Machine Learning can be very mathematical. The mathematics for each area is introduced in a clear and concise form so that even casual readers can understand the math. Readers from all areas of engineering will see connections to what they know and will learn new technology. The book then provides complete solutions in MATLAB for several important problems in machine learning including face identification, autonomous driving, and data classification. Full source code is provided for all of the examples and applications in the book. What you'll learn: An overview of the field of machine learning Commercial and open source packages in MATLAB How to use MATLAB for programming and building machine learning applications MATLAB graphics for machine learning Practical real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.




Wavefront Optics for Vision Correction


Book Description

This book addresses some of the issues in visual optics with a functional analysis of ocular aberrations, especially for the purpose of vision correction. The basis is the analytical representation of ocular aberrations with a set of orthonormal polynomials, such as Zernike polynomials or the Fourier series. Although the aim of this book is the application of wavefront optics to laser vision correction, most of the theories discussed are equally applicable to other methods of vision correction, such as contact lenses and intraocular lenses.