Josh Holmes

Successfully and proactively take charge of your machine learning strategy. Machine learning (ML) is permeating every sector and aspect of business, from evaluating the success of a massive online marketing campaign, to predicting insurance payouts, to crime scene analysis. This book shows how to interpret patterns and redundancies from massive amounts of existing data to help your business cut costs, operate more efficiently and effectively, and get to the next level. You will learn how to analyze, communicate, and launch a viable program that, when done correctly, will positively transform your business. The authors engage you to experience the business of machine learning through actual conversations that open with an exchange between a data scientist and and his counterpart in business, the technical decision maker. You will learn where to go when the conversation leads to an impasse and work step-by-step to methodically resolve the challenges. After reading this book, you will come away with the confidence to tackle a machine learning strategy customized for your team or business objectives. Revel in the vast capabilities of machine learning tools at your disposal and reach that "a ha" moment when you discover the profound and enduring impact machine learning can have on your business. What You'll LearnUnderstand the vast potential of machine learning, and how and when to apply different ML techniquesDevise strategies to improve efficiency and accuracy in your businessGet to know your customers and their specific needs through interpreting highly accurate and complex dataCommunicate more effectively with teams of architects and data scientists as they develop and deploy complex machine learning solutions Contrast the life cycle of a machine learning project to a software development project Master terms such as “convolutional neural network,” “nonparametric regression,” and “multi-class decision jungle”Who This Book is ForAny technical business decision maker who has to implement a machine learning strategy or converse with data scientists. A basic level of technical understanding is helpful, but does not have to be specific to programming languages or operating systems. This book is open access under a CC BY license.

At first glance, building and deploying applications seem simple enough. But in fact, difficult releases without any confidence or processes backing them are very common. Integration and management of a new deployment can be laborious and fraught with risk. So as team size and volume of projects grow, management becomes more difficult and risk more pronounced. This book is a guide to the implementation of good processes in a . NET environment. Author Marc Holmes focuses on actual implementation, and details patterns and anti-patterns to watch out for. He also provides a practical and in-depth look at NAnt and CruiseControl. NET, and solutions to common problem scenarios. For additional insights, visit the author's blog, Marc: My Words.

At first glance, building and deploying applications seem simple enough. But in fact, difficult releases without any confidence or processes backing them are very common. Integration and management of a new deployment can be laborious and fraught with risk. So as team size and volume of projects grow, management becomes more difficult and risk more pronounced. This book is a guide to the implementation of good processes in a . NET environment. Author Marc Holmes focuses on actual implementation, and details patterns and anti-patterns to watch out for. He also provides a practical and in-depth look at NAnt and CruiseControl. NET, and solutions to common problem scenarios. For additional insights, visit the author's blog, Marc: My Words.