Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game--soccer--to illuminate key concepts in predictive modeling and data science. You'll develop a solid foundation in machine learning through engaging examples that bridge academic principles with practical applications.Written by experts in both machine learning and sports analytics, this practical Python-focused guide intro...

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for ...

"Statistical Methods in Online A/B Testing" is a comprehensive guide to statistics in online controlled experiments, a.k.a. A/B tests, that tackles the difficult matter of statistical inference in a way accessible to readers with little to no prior experience with it. Each concept is built from the ground up, explained thoroughly, and illustrated with practical examples from website testing.The presentation is straight to the point and practically oriented so you can apply the take...

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share n...

200+ pages of valuable content!Machines can LEARN?!?!Machine learning occurs primarily through the use of " algorithms" and other elaborate procedures.Whether you're a novice, intermediate or expert this book will teach you all the ins, outs and everything you need to know about machine learning.Note: Bonus chapters included inside!Instead of spending hundreds or even thousands of dollars on courses/materials why not read this book instead? Its a wor...

Get your statistics basics right before diving into the world of data science Key FeaturesNo need to take a degree in statistics, read this book and get a strong statistics base for data science and real-world programs;Implement statistics in data science tasks such as data cleaning, mining, and analysisLearn all about probability, statistics, numerical computations, and more with the help of R programsBook DescriptionData sc...

Gain practical insights by exploiting data in your business to build advanced predictive modeling applicationsKey FeaturesA step-by-step guide to predictive modeling including lots of tips, tricks, and best practicesLearn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and ClusteringMaster open source Python tools to build sophisticated predictive models...

Key FeaturesBook DescriptionUpdated and upgraded to the latest libraries and most modern thinking, Machine Learning with R, Second Edition provides you with a rigorous introduction to this essential skill of professional data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with minimal previous experience. With this book, you'll discover...

Get better insights from time-series data and become proficient in model performance analysisKey FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time series via real-world case studies on operations management, digital marketing, finance, and healthcareBook ...

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...

Learn how to use data science and Python to solve everyday business problems.Dive into the exciting world of data science with this practical introduction. Packed with essential skills and useful examples, Dive Into Data Science will show you how to obtain, analyze, and visualize data so you can leverage its power to solve common business challenges.With only a basic understanding of Python and high school math, you’ll be able to effortlessly work ...

Now***,*** a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications.Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation,...