With Britain by late 1916 facing the prospect of an economic crisis and increasingly dependent on the US, rival factions in Asquith's government battled over whether or not to seek a negotiated end to the First World War. In this riveting new account, Daniel Larsen tells the full story for the first time of how Asquith and his supporters secretly sought to end the war. He shows how they supported President Woodrow Wilson's efforts to convene a peace conference and how British intelligence, clandestinely breaking American codes, aimed to sabotage these peace efforts and aided Asquith's rivals. With Britain reading and decrypting all US diplomatic telegrams between Europe and Washington, these decrypts were used in a battle between the Treasury, which was terrified of looming financial catastrophe, and Lloyd George and the generals. This book's findings transform our understanding of British strategy and international diplomacy during the war.
This book teaches the full process of how to conduct machine learning in an organizational setting. It develops the problem-solving mind-set needed for machine learning and takes the reader through several exercises using an automated machine learning tool. To build experience with machine learning, the book provides access to the industry-leading AutoML tool, DataRobot, and provides several data sets designed to build deep hands-on knowledge of machinelearning.
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