Téléchargez le livre : Machine Learning for Economics and Finance in TensorFlow 2

Machine Learning for Economics and Finance in TensorFlow 2

Deep Learning Models for Research and Industry

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Éditeur :

Apress


Paru le : 2020-11-25



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Description

Machine learning has taken time to move into the space of academic economics. This is because empirical research in economics is concentrated on the identification of causal relationships in parsimonious statistical models; whereas machine learning is oriented towards prediction and is generally uninterested in either causality or parsimony. That leaves a gap for students, academics, and professionals who lack a standard reference on machine learning for economics and finance.




This book focuses on economic and financial problems with an empirical dimension, where machine learning methods may offer something of value. This includes coverage of a variety of discriminative deep learning models (DNNs, CNNs, LSTMs, and DQNs), generative machine learning models (GANs and VAEs), and tree-based models. It also covers the intersection of empirical methods in economics and machine learning, including regression analysis, natural language processing, and dimensionality reduction.




TensorFlow offers a toolset that can be used to define and solve any graph-based model, including those commonly used in economics. This book is structured to teach through a sequence of complete examples, each framed in terms of a specific economic problem of interest or topic. This simplifies otherwise complicated concepts, enabling the reader to solve workhorse theoretical models in economics and finance using TensorFlow.



What You'll Learn
Define, train, and evaluate machine learning models in TensorFlow 2Apply fundamental concepts in machine learning, such as deep learning and natural language processing, to economic and financial problems Solve theoretical models in economics


Who This Book Is For


Students, data scientists working in economics and finance, public and private sector economists, and academic social scientists
Pages
368 pages
Collection
n.c
Parution
2020-11-25
Marque
Apress
EAN papier
9781484263723
EAN PDF
9781484263730
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
36
Taille du fichier
6011 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
62,11 €
EAN EPUB
9781484263730
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
36
Taille du fichier
15084 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
62,11 €

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