Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
The Data Science Design Manual (Texts in Computer Science)

Buy

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)
(HTML tags aren't allowed.)

Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed...
The Job Interview Phrase Book: The Things to Say to Get You the Job You Want
The Job Interview Phrase Book: The Things to Say to Get You the Job You Want

"In today's marketplace it is critical that you stand out in a crowd."
--Eric Winegardener, Vice President, Monster Worldwide

In today's tightening job market, the interview is a key stage. But too often in job interviews, candidates freeze and can't find the words they need to make...

JavaScript: The Good Parts
JavaScript: The Good Parts

Most programming languages contain good and bad parts, but JavaScript has more than its share of the bad, having been developed and released in a hurry before it could be refined. This authoritative book scrapes away these bad features to reveal a subset of JavaScript that's more reliable, readable, and maintainable than the language as a...


Introduction to Hilbert Spaces with Applications
Introduction to Hilbert Spaces with Applications
The Second Edition if this successful text offers a systematic exposition of the basic ideas and results of Hilbert space theory and functional analysis. It includes a simple introduction to the Lebesgue integral and a new chapter on wavelets. The book provides the reader with revised examples and updated diverse applications to differential and...
The Linear Algebra a Beginning Graduate Student Ought to Know
The Linear Algebra a Beginning Graduate Student Ought to Know

Linear algebra is a living, active branch of mathematics which is central to almost all other areas of mathematics, both pure and applied, as well as to computer science, to the physical, biological, and social sciences, and to engineering. It encompasses an extensive corpus of theoretical results as well as a large and rapidly-growing body...

Data Science: Innovative Developments in Data Analysis and Clustering (Studies in Classification, Data Analysis, and Knowledge Organization)
Data Science: Innovative Developments in Data Analysis and Clustering (Studies in Classification, Data Analysis, and Knowledge Organization)

This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection...

©2018 LearnIT (support@pdfchm.net) - Privacy Policy