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Fundamentals of Machine Learning for Predictive Data Analytics, second edition
The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.
How to Be Massive
You know your one Nikita? You've seen her around town: always within 100 metres of Penneys (where she likes to spend her 'eurdos'), her hair done up in a 'hun bun', sporting her 'masso' runners and her eyebrows on fleek. In How to be Massive Nikita shares her illustrated guide to being massive, from masso make-up to stunnin' accessories, the vital difference between your 'going out' and 'staying in' PJs, as well as life hacks such as places to hide your naggin and how to whiten your runners with toothpaste. Through her popular Instagram account Your One Nikita, illustrator Aoife Dooley has made the spicebag part of our everyday language. Informed by her experiences growing up in Coolock and affectionately parodying fiery working-class Dublin women, it provides the inspiration for her hilarious and brilliantly observed first book, How to Be Massive. C'mon ya pox, buy the book 'Razor-sharp observational humour ... has the zeitgeisty quotability of a contemporary Roddy Doyle.' The Irish Times 'How to Be Massive is funny, affectionate and very, very sharp. Almost social history and always great fun, this book is, well, massive.' Roddy Doyle
Seven Signs of Life
'Heartfelt, honest, illuminating and wise' Julia Samuel, author of This Too Shall Pass. Perfect for fans of This Is Going to Hurt. Grief. Anger. Joy. Fear. Distraction. Disgust. Hope. All emotions we expect to encounter over our lifetime. But what if this was every day? And what if your ability to manage them was the difference between life and death? For Aoife Abbey, a doctor in intensive care, these experiences are part of the job - from grief when you make a potentially fatal mistake to joy when the ward unexpectedly breaks into song. Seven Signs of Life is Abbey's extraordinary account of what it means to be alive and how it feels to care for a living. An insightful, tender and inspiring memoir that explores the reality of life on the NHS front line. 'Brilliant, compelling... A hugely life-affirming book' Mail on Sunday
Data Science
A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. It has ne...
Cybersecurity Analytics
Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.
Learning to Play
In this textbook the author takes as inspiration recent breakthroughs in game playing to explain how and why deep reinforcement learning works. In particular he shows why two-person games of tactics and strategy fascinate scientists, programmers, and game enthusiasts and unite them in a common goal: to create artificial intelligence (AI). After an introduction to the core concepts, environment, and communities of intelligence and games, the book is organized into chapters on reinforcement learning, heuristic planning, adaptive sampling, function approximation, and self-play. The author takes a hands-on approach throughout, with Python code examples and exercises that help the reader understa...
Computational Analysis of Communication
Provides clear guidance on leveraging computational techniques to answer social science questions In disciplines such as political science, sociology, psychology, and media studies, the use of computational analysis is rapidly increasing. Statistical modeling, machine learning, and other computational techniques are revolutionizing the way electoral results are predicted, social sentiment is measured, consumer interest is evaluated, and much more. Computational Analysis of Communication teaches social science students and practitioners how computational methods can be used in a broad range of applications, providing discipline-relevant examples, clear explanations, and practical guidance. As...
The Art of Feature Engineering
When machine learning engineers work with data sets, they may find the results aren't as good as they need. Instead of improving the model or collecting more data, they can use the feature engineering process to help improve results by modifying the data's features to better capture the nature of the problem. This practical guide to feature engineering is an essential addition to any data scientist's or machine learning engineer's toolbox, providing new ideas on how to improve the performance of a machine learning solution. Beginning with the basic concepts and techniques, the text builds up to a unique cross-domain approach that spans data on graphs, texts, time series, and images, with fully worked out case studies. Key topics include binning, out-of-fold estimation, feature selection, dimensionality reduction, and encoding variable-length data. The full source code for the case studies is available on a companion website as Python Jupyter notebooks.
Predictive Analytics
"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Com...
Handbook of the Language Industry
Digital transformation and demographic change are profoundly affecting the contexts in which the language industry operates, the resources it deploys and the roles and skillsets of those it employs. Driven by evolving digital resources and socio-ethical demands, the roles and responsibilities deriving from the proliferation of new and emerging profiles in the language industry are transcending the traditional bounds of core activities and competences associated with prototypical concepts of translation and interpreting. This volume focuses on the realities in the language industry from the fresh perspective of current and emerging professional profiles and of the contexts and resources that ...
