內容簡介:啟動你的機器學習與資料科學職涯「這是一本關於機器學習面試的全方位指南。本書涵蓋了大多數機器學習面試的內容，對於該領域的新手、經驗豐富的機器學習（ML）從業者以及資料科學家來說，都非常實用。」--Prithvishankar SrinivasanInstacart的ML工程師（曾任職於Twitter、Microsoft）隨著現今科技產品日益普及，對機器學習專業人才的需求也持續成長。但是不同公司之間對於ML專業人員的職責和技能要求差異迥然不同，使得面試過程難以預測。在本書中，資料科學領導者Susan Shu Chang將為你揭示如何成功應對ML招募過程的每一項挑戰。Susan Shu Chang曾任職於多間公司的首席資料科學家，無論是擔任ML 面試官或身為應試者的身分，都擁有相當豐富的經驗。藉由本書，她分享自己在這整個過程中學到的寶貴心得，向你說明這個具高度選擇性的招募過程，讓您能快速掌握典型ML面試的成功秘訣。這本書將帶您了解：•探索各種機器學習職位，涵蓋ML工程師、應用科學家、資料科學家和其他相關職位。•在決定要將何種ML職位設定為目標前，先評估自己的興趣和技能。•衡量自己目前的技術水準，針對阻礙面試成功的弱項進行補強。•取得每個ML職位需要的技能，並製作適用於應徵的履歷表。•在編碼測試、統計和ML理論、以及行為問題等ML面試主題上輕鬆得分。•透過研究常見的ML面試模式和提問，為面試做好充足準備。•獲取面試後的提示和其他有價值的資源。
Frontiers of Memory in the Asia-Pacific explores the making and consumption of conflict-related heritage throughout the Asia-Pacific region. Contributing to a growing literature on ‘difficult heritage’, this collection advances our understanding of how places of pain, shame, oppression, and trauma have been appropriated and refashioned as ‘heritage’ in a number of societies in contemporary East and Southeast Asia and Oceania. The authors analyse how the repackaging of difficult pasts as heritage can serve either to reinforce borders, transcend them, or even achieve both simultaneously, depending on the political agendas that inform the heritage-making process. They also examine the ways in which these processes respond to colonialism, decolonization, and nationalism. The volume shows how efforts to preserve various sites of ‘difficult heritage’ can involve the construction of new borders in the mind between what is commemorated and what is often deliberately obscured or forgotten. Take
