Eric Carter

Eric Lippert

Visual Studio Tools for Office is both the first and the definitive book on VSTO 2005 programming, written by the inventors of the technology. VSTO is a set of tools that allows professional developers to use the full power of Visual Studio .NET and the .NET Framework to put code behind Excel 2003, Word 2003, Outlook 2003, and InfoPath 2003. VSTO provides functionality never before available to the Office developer: data binding and data/view separation, design-time views of Excel and Word documents inside Visual Studio, rich support for Windows Forms controls in a document, the ability to create custom Office task panes, server-side programming support against Office, and much more. Carter and Lippert cover their subject matter with deft insight into the needs of .NET developers learning VSTO. This book Explains the architecture of Microsoft Office programming and introduces the object models Teaches the three basic patterns of Office solutions: Office automation executables, Office add-ins, and code behind a document Explores the ways of customizing Excel, Word, Outlook, and InfoPath, and plumbs the depths of programming with their events and object models Introduces the VSTO programming model Teaches how to use Windows Forms in VSTO and how to work with the Actions Pane Delves into VSTO data programming and server data scenarios Explores .NET code security and VSTO deployment

Using Visual Basic 2005 with Excel, Word, Outlook, and InfoPath

Visual Studio Tools for Office

Anthony Loveless

Second World War fighter pilot Eric Carter is one of only four surviving members of a secret mission, code-named 'Force Benedict'. Sanctioned by Winston Churchill in 1941 Force Benedict was dispatched to defend Murmansk, the USSR's only port not under Nazi occupation. If Murmansk fell, Soviet resistance against the Nazis would be hard to sustain and Hitler would be able to turn all his forces on Britain... Force Benedict was under the command of New Zealand-born RAF Wing Commander Henry Neville Gynes Ramsbottom-Isherwood, who led two squadrons of Hurricane fighters, pilots and ground crew which were shipped to Russia in total secrecy on the first ever Arctic Convoy. They were told to defend Murmansk against the Germans 'at all costs'. 'We all reckoned the government thought we'd never survive' - but Eric Carter did, and was threatened with Court Martial if he talked about where he'd been or what he'd done. Now he reveals his experiences of seventy years ago in the hell on earth that was Murmansk, the largest city north of the Arctic Circle. It will also include previously unseen photos and documents, as well as exploring - for the first time - other intriguing aspects of Force Benedict.

Force Benedict

Matthew Hurst

Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto. Bringing together talented people to create a great applied machine learning team is no small feat. With developers and data scientists both contributing expertise in their respective fields, communication alone can be a challenge. Agile Machine Learning teaches you how to deliver superior data products through agile processes and to learn, by example, how to organize and manage a fast-paced team challenged with solving novel data problems at scale, in a production environment. The authors’ approach models the ground-breaking engineering principles described in the Agile Manifesto. The book provides further context, and contrasts the original principles with the requirements of systems that deliver a data product. What You'll Learn Effectively run a data engineering team that is metrics-focused, experiment-focused, and data-focused Make sound implementation and model exploration decisions based on the data and the metrics Know the importance of data wallowing: analyzing data in real time in a group setting Recognize the value of always being able to measure your current state objectively Understand data literacy, a key attribute of a reliable data engineer, from definitions to expectations Who This Book Is For Anyone who manages a machine learning team, or is responsible for creating production-ready inference components. Anyone responsible for data project workflow of sampling data; labeling, training, testing, improving, and maintaining models; and system and data metrics will also find this book useful. Readers should be familiar with software engineering and understand the basics of machine learning and working with data.

Eric Carter

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