{"product_id":"machine-learning-for-economics-and-finance-in-tensorflow-2-deep-learning-models-for-research-and-industry-9781484263723","title":"Machine Learning for Economics and Finance in Tensorflow 2: Deep Learning Models for Research and Industry","description":"\u003cp\u003e\u003ci\u003eChapter 1: TensorFlow 2.0\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter Goal: Introduce TensorFlow 2 and discuss preliminary material on conventions and practices specific to TensorFlow. \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eDifferences between TensorFlow iterations\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eTensorFlow for economics and finance\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eIntroduction to tensors\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eReview of linear algebra and calculus\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eLoading data for use in TensorFlow\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eDefining constants and variables\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter 2: Machine Learning and Economics\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter Goal: Provide a high-level overview of machine learning models and explain how they can be employed in economics and finance. Part of the chapter will review existing work in economics and speculate on future use-cases.\u003c\/i\u003e\u003c\/p\u003e- \u003ci\u003eIntroduction to machine learning\u003c\/i\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eMachine learning for economics and finance\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eUnsupervised machine learning\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eSupervised machine learning\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eRegularization\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003ePrediction\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eEvaluation\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter 3: Regression\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter Goal: Explain how regression models are used primarily for prediction purposes in machine learning, rather than hypothesis testing, as is the case in economics. Introduce evaluation metrics and optimization routines used to solve regression models. \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eLinear regression\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003ePartially-linear regression\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eNon-linear regression\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eLogistic regression\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eLoss functions\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eEvaluation metrics\u003c\/i\u003e\u003c\/p\u003e- \u003ci\u003eOptimizers\u003c\/i\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter 4: Trees\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter Goal: Introduce tree-based models and the concept of ensembles.\u003c\/i\u003e\u003c\/p\u003e- \u003ci\u003eDecision trees\u003c\/i\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eRegression trees\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eRandom forests\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eModel tuning\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter 5: Gradient Boosting\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter Goal: Introduce gradient boosting and discuss how it is applied, how models are tuned, and how to identify important features.\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eIntroduction to gradient boosting\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eBoosting with regression models\u003c\/i\u003e\u003c\/p\u003e- \u003ci\u003eBoosting with trees\u003c\/i\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eModel tuning\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eFeature importance\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003e \u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter 6: Images\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eChapter Goal: Introduce the high level Keras and Estimators APIs. Explain how these libraries can be used to perform image classification using a variety of deep learning models. Also, discuss the use of pretrained models and fine-tuning. Speculate on image classification uses in economics and finance.\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eKeras\u003c\/i\u003e\u003c\/p\u003e- \u003ci\u003eEstimators\u003c\/i\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eData preparation\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e- \u003ci\u003eDeep neural networ\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-13779997\"\u003eIsaiah Hull\u003c\/a\u003e\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Apress\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 11\/26\/2020\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 368\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.18lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.21h x 6.14w x 0.79d\u003cbr\u003e\u003cb\u003eISBN13:\u003c\/b\u003e 9781484263723\u003cbr\u003e\u003cb\u003eISBN10:\u003c\/b\u003e 1484263723\u003cbr\u003e\u003cb\u003eBISAC Categories:\u003c\/b\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM004000\"\u003eArtificial Intelligence | General\u003c\/a\u003e\u003cbr\u003e\u003cbr\u003e\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eIsaiah Hull\u003c\/b\u003e received his PhD in Economics from Boston College in 2013 and has since worked in the Research Division at Sweden's Central Bank. He has published numerous articles in academic journals primarily concentrated in computational economics with applications in macroeconomics, finance, and housing. Most of his recent work makes use of techniques from machine learning. He also regularly presents at conferences on machine learning and big data in economics. And Isaiah is an accomplished teacher with experience teaching TensorFlow 2.0. Currently, he's working on a project to introduce quantum computing to economists.\u003c\/p\u003e","brand":"Apress","offers":[{"title":"Default Title","offer_id":45876729610415,"sku":"9781484263723","price":64.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0651\/9255\/8767\/files\/img_867b9958-0cc7-4d20-941a-66eab76ab51c.jpg?v=1757694659","url":"https:\/\/www.correctionsbookstore.com\/es\/products\/machine-learning-for-economics-and-finance-in-tensorflow-2-deep-learning-models-for-research-and-industry-9781484263723","provider":"Corrections Bookstore ","version":"1.0","type":"link"}