Bøger af Gareth James

Football's Fifty Most Important Clubs journeys into the history of the beautiful game, exploring the successes, failures and innovations of the world's most influential clubs. This history of football's big teams helps us to better understand not only the current state of play, but the wider world around it.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

We here at Hashtag Blogger have teamed up with internet sensation Rumena Begum to provide you with 'Blogging Made Easy'. We have written the guides in this book to help you make the most out of life as a blogger in 2016 and help you take your success to the next level by attracting more visitors and increasing your online exposure. Whether you're starting up a new blog, have done blogging for years, or you're running a blog for your business. We're going to cover everything you need to know in order to have a successful online blog. We'll also explain how you can outreach and get noticed by brands looking for collaborations.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R(ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

The Final Table will teach you how to make great decisions at every stage at the business end of the tournament. It will also set out a program so you can learn how to continuously improve your final table strategy every single day.

This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.

Norwich City On This Day revisits all the most magical and memorable moments from the club's rollercoaster history, mixing in a maelstrom of quirky anecdotes and legendary characters to produce an irresistibly dippable Canaries diary. From City's formation in 1902 to the Premier League era, there's an entry for every day of the year.