Machine Learning for Economics and Finance in TensorFlow 2

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  • Author : Isaiah Hull
  • Publisher : Apress
  • Pages : 368 pages
  • ISBN : 9781484263723
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Machine Learning for Economics and Finance in TensorFlow 2

Download or Read online Machine Learning for Economics and Finance in TensorFlow 2 full in PDF, ePub and kindle. this book written by Isaiah Hull and published by Apress which was released on 26 November 2020 with total page 368 pages. We cannot guarantee that Machine Learning for Economics and Finance in TensorFlow 2 book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Work on economic problems and solutions with tools from machine learning. ML has taken time to move into the space of academic economics. This is because empirical work 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 both students and professionals in the economics industry without a standard reference. This book focuses on economic 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, RNNs, LSTMs, the Transformer Model, etc.), generative machine learning models, random forests, gradient boosting, clustering, and feature extraction. You'll also learn about the intersection of empirical methods in economics and machine learning, including regression analysis, text analysis, and dimensionality reduction methods, such as principal components analysis. TensorFlow offers a toolset that can be used to setup and solve any mathematical 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. Otherwise complicated content is then distilled into accessible examples, so you can use TensorFlow to solve workhorse models in economics and finance. What You'll Learn Define, train, and evaluate machine learning models in TensorFlow 2 Apply fundamental concepts in machine learning, such as deep learning and natural language processing, to economic and financial problems Solve workhorse models in economics and finance Who This Book Is For Students and data scientists working in the economics industry. Academic economists and social scientists who have an interest in machine learning are also likely to find this book useful.

Machine Learning for Economics and Finance in TensorFlow 2

Machine Learning for Economics and Finance in TensorFlow 2
  • Author : Isaiah Hull
  • Publisher : Apress
  • Release : 26 November 2020
GET THIS BOOK Machine Learning for Economics and Finance in TensorFlow 2

Work on economic problems and solutions with tools from machine learning. ML has taken time to move into the space of academic economics. This is because empirical work 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 both students and professionals in the economics industry without a standard reference. This book focuses on economic

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  • Publisher : Packt Publishing Ltd
  • Release : 21 November 2017
GET THIS BOOK Machine Learning with TensorFlow 1 x

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  • Release : 31 July 2020
GET THIS BOOK Machine Learning for Algorithmic Trading

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GET THIS BOOK Machine Learning for Factor Investing R Version

Machine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers, notably for alpha signal generation and stocks selection. The technicality of the subject can make it hard for non-specialists to join the bandwagon, as the jargon and coding requirements may seem out of reach. Machine Learning for Factor Investing: R Version bridges this gap. It provides a comprehensive tour of modern ML-based investment strategies that

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  • Publisher : Packt Publishing Ltd
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GET THIS BOOK Artificial Intelligence with Python Cookbook

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  • Publisher : O'Reilly Media
  • Release : 14 October 2019
GET THIS BOOK Practical Deep Learning for Cloud Mobile and Edge

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  • Publisher : McGraw Hill Professional
  • Release : 29 April 2021
GET THIS BOOK Machine Learning and Deep Learning Using Python and TensorFlow

Understand the principles and practices of machine learning and deep learning This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in

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  • Publisher : Packt Publishing Ltd
  • Release : 31 December 2018
GET THIS BOOK Data Analysis with Python

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