Book picks similar to
Evolutionary Optimization Algorithms by Dan Simon


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operations-research-optimization
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Turning Numbers into Knowledge: Mastering the Art of Problem Solving


Jonathan G. Koomey - 2003
    In addition to containing numerous updates to the contents—references, URLs, and reading lists—this second edition includes a new foreword, revised chapters, and an epilogue. Mastering the art of problem solving takes more than proficiency with basic calculations; it requires understanding how people use information, recognizing the importance of ideology, learning the art of storytelling, and acknowledging the important distinction between facts and values. Intended for executives, professors, and students, this guide addresses these and other essential skills.

The Old Farmer's Almanac 2016


Old Farmer's Almanac - 2015
    Thomas, and readers’ expectations. This edition is packed with wit, wisdom, tips, advice, facts, fun, and recipes, including: • traditionally 80 percent–accurate weather forecasts • how to make sausages at home • “creatures from hell” • grow your own beer (ingredients) • time- and money-saving tips • unmasked mysteries of plant seed dispersal • bale, key, and concrete block gardens • quirky origins of American horse breeds • history, lore, and more about birthstones Plus, Moon phases and other celestial sightings, tides, gardening tables, best days to do things, and more.   Added value this year: • 96 full-color pages • full-color winter and summer weather maps • updated Reference section Often imitated, but never equaled. Accept no substitutes!

Machine Learning: The Art and Science of Algorithms That Make Sense of Data


Peter Flach - 2012
    Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

Introduction to Machine Learning with Python: A Guide for Data Scientists


Andreas C. Müller - 2015
    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

The Youtube Formula: How Anyone Can Unlock the Algorithm to Drive Views, Build an Audience, and Grow Revenue


Derral Eves - 2021
    In The YouTube Formula: How Anyone Can Unlock the Algorithm to Drive Views, Build an Audience, and Grow Revenue, the owner of the largest YouTube how-to channel provides the secrets to getting the results that every YouTube creator and strategist wants. Eves will reveal what readers can't get anywhere else: the inner workings of the YouTube algorithm that's responsible for determining success on the platform, and how creators can use it to their advantage.Full of actionable advice and concrete strategies, this book teaches readers how to:Launch a channel Create life-changing content Drive rapid view and subscriber growth Build a brand and increase engagement Improve searchability Monetize content and audience Replete with case studies and information from successful YouTube creators, The YouTube Formula is perfect for any creator, entrepreneur, social media strategist, and brand manager who hopes to see real commercial results from their work on the platform.