The ABCs of Data Science - By Real Data Scientists, For Future Data Scientists

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

Florence the Data Scientist and Her Magical Bookmobile is a picture book for young readers that explores and explains one of today's most important and fastest-growing professions: data science! How can recording and analyzing data for patterns help make predictions about the future? Join Beatrice as she finds out. Beatrice loves four different things: reading, science, dragons, and swings! When a mysterious bookmobile drives down her street, the driver Florence knows exactly what books will delight all the kids in the neighborhood. But how?! Beatrice watches the scene throughout the day to record and analyze each of her friend's responses to Florence's same questions. Is Florence a psychic? Or is there a logical pattern at play? Can Beatrice ensure she answers to get the outcome she craves? Florence the Data Scientist helps young readers (and their parents!) understand the amazing predictive power of recording and analyzing trends and data.

Science, with its inherent tension between the known and the unknown, is an inexhaustible mine of great stories. Collected here are twenty-six among the most enchanting tales, one for each letter of the alphabet: the main characters are scientists of the highest caliber most of whom, however, are unknown to the general public. This book goes from A to Z. The letter A stands for Abel, the great Norwegian mathematician, here involved in an elliptic thriller about a fundamental theorem of mathematics, while the letter Z refers to Absolute Zero, the ultimate and lowest temperature limit, - 273,15 degrees Celsius, a value that is tremendously cooler than the most remote corner of the Universe: the race to reach this final outpost of coldness is not yet complete, but, similarly to the history books of polar explorations at the beginning of the 20th century, its pages record successes, failures, fierce rivalries and tragic desperations. In between the A and the Z, the other letters of the alphabet are similar to the various stages of a very fascinating journey along the paths of science, a journey in the company of a very unique set of characters as eccentric and peculiar as those in Ulysses by James Joyce: the French astronomer who lost everything, even his mind, to chase the transits of Venus; the caustic Austrian scientist who, perfectly at ease with both the laws of psychoanalysis and quantum mechanics, revealed the hidden secrets of dreams and the periodic table of chemical elements; the young Indian astrophysicist who was the first to understand how a star dies, suffering the ferocious opposition of his mentor for this discovery. Or the Hungarian physicist who struggled with his melancholy in the shadows of the desert of Los Alamos; or the French scholar who was forced to hide her femininity behind a false identity so as to publish fundamental theorems on prime numbers. And so on and so forth. Twenty-six stories, which reveal the most authentic atmosphere of science and the lives of some of its main players: each story can be read in quite a short period of time -- basically the time it takes to get on and off the train between two metro stations. Largely independent from one another, these twenty-six stories make the book a harmonious polyphony of several voices: the reader can invent his/her own very personal order for the chapters simply by ordering the sequence of letters differently. For an elementary law of Mathematics, this can give rise to an astronomically large number of possible books -- all the same, but - then again - all different. This book is therefore the ideal companion for an infinite number of real or metaphoric journeys.

Selected as one of NPR's Best Books of 2016, this book offers superior learning tools for teachers and students, from A to Z. An explosive growth in research on how people learn has revealed many ways to improve teaching and catalyze learning at all ages. The purpose of this book is to present this new science of learning so that educators can creatively translate the science into exceptional practice. The book is highly appropriate for the preparation and professional development of teachers and college faculty, but also parents, trainers, instructional designers, psychology students, and simply curious folks interested in improving their own learning. Based on a popular Stanford University course, The ABCs of How We Learn uses a novel format that is suitable as both a textbook and a popular read. With everyday language, engaging examples, a sense of humor, and solid evidence, it describes 26 unique ways that students learn. Each chapter offers a concise and approachable breakdown of one way people learn, how it works, how we know it works, how and when to use it, and what mistakes to avoid. The book presents learning research in a way that educators can creatively translate into exceptional lessons and classroom practice. The book covers field-defining learning theories ranging from behaviorism (R is for Reward) to cognitive psychology (S is for Self-Explanation) to social psychology (O is for Observation). The chapters also introduce lesser-known theories exceptionally relevant to practice, such as arousal theory (X is for eXcitement). Together the theories, evidence, and strategies from each chapter can be combined endlessly to create original and effective learning plans and the means to know if they succeed.

A rhyming children's storybook that uses a dog-filled analogy to provide an accessible definition of data science. Mia is a young girl that loves to learn. With her dog, Bowie, she goes on an adventure to learn everything about every dog in the world. Along the way, she finds out that the challenge is bigger than she thought, and she might just need a helping hand... or keyboard!

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)