Machine learning Techniques in Economics

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  • Author : Atin Basuchoudhary
  • Publisher : Springer
  • Pages : 94 pages
  • ISBN : 3319690140
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Machine learning Techniques in Economics

Download or Read online Machine learning Techniques in Economics full in PDF, ePub and kindle. this book written by Atin Basuchoudhary and published by Springer which was released on 28 December 2017 with total page 94 pages. We cannot guarantee that Machine learning Techniques in Economics 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. This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer economic questions. While machine learning itself is not a new idea, advances in computing technology combined with a dawning realization of its applicability to economic questions makes it a new tool for economists.

Machine learning Techniques in Economics

Machine learning Techniques in Economics
  • Author : Atin Basuchoudhary,James T. Bang,Tinni Sen
  • Publisher : Springer
  • Release : 28 December 2017
GET THIS BOOK Machine learning Techniques in Economics

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer economic questions. While machine learning itself is not a new idea, advances in computing technology combined with a dawning realization of its applicability to economic questions makes it a new tool for economists.

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

Machine Learning Techniques for Improved Business Analytics

Machine Learning Techniques for Improved Business Analytics
  • Author : G., Dileep Kumar
  • Publisher : IGI Global
  • Release : 06 July 2018
GET THIS BOOK Machine Learning Techniques for Improved Business Analytics

Analytical tools and algorithms are essential in business data and information systems. Efficient economic and financial forecasting in machine learning techniques increases gains while reducing risks. Providing research on predictive models with high accuracy, stability, and ease of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning Techniques for Improved Business Analytics is a collection of innovative research on the methods and applications of artificial intelligence in strategic business decisions and management. Featuring

An Algorithmic Crystal Ball Forecasts based on Machine Learning

An Algorithmic Crystal Ball  Forecasts based on Machine Learning
  • Author : Jin-Kyu Jung,Manasa Patnam,Anna Ter-Martirosyan
  • Publisher : International Monetary Fund
  • Release : 01 November 2018
GET THIS BOOK An Algorithmic Crystal Ball Forecasts based on Machine Learning

Forecasting macroeconomic variables is key to developing a view on a country's economic outlook. Most traditional forecasting models rely on fitting data to a pre-specified relationship between input and output variables, thereby assuming a specific functional and stochastic process underlying that process. We pursue a new approach to forecasting by employing a number of machine learning algorithms, a method that is data driven, and imposing limited restrictions on the nature of the true relationship between input and output variables. We

Handbook of the Economics of Marketing

Handbook of the Economics of Marketing
  • Author : Anonim
  • Publisher : North Holland
  • Release : 15 September 2019
GET THIS BOOK Handbook of the Economics of Marketing

Handbook of the Economics of Marketing, Volume One: Marketing and Economics mixes empirical work in industrial organization with quantitative marketing tools, presenting tactics that help researchers tackle problems with a balance of intuition and skepticism. It offers critical perspectives on theoretical work within economics, delivering a comprehensive, critical, up-to-date, and accessible review of the field that has always been missing. This literature summary of research at the intersection of economics and marketing is written by, and for, economists, and the

Behavioral Predictive Modeling in Economics

Behavioral Predictive Modeling in Economics
  • Author : Songsak Sriboonchitta,Vladik Kreinovich,Woraphon Yamaka
  • Publisher : Springer Nature
  • Release : 05 August 2020
GET THIS BOOK Behavioral Predictive Modeling in Economics

This book presents both methodological papers on and examples of applying behavioral predictive models to specific economic problems, with a focus on how to take into account people's behavior when making economic predictions. This is an important issue, since traditional economic models assumed that people make wise economic decisions based on a detailed rational analysis of all the relevant aspects. However, in reality – as Nobel Prize-winning research has shown – people have a limited ability to process information and, as a

Dissecting Characteristics via Machine Learning for Stock Selection

Dissecting Characteristics via Machine Learning for Stock Selection
  • Author : David Dümig
  • Publisher : GRIN Verlag
  • Release : 31 January 2020
GET THIS BOOK Dissecting Characteristics via Machine Learning for Stock Selection

Academic Paper from the year 2019 in the subject Business economics - Investment and Finance, , language: English, abstract: We conduct a comparative analysis of methods in the machine learning repertoire, including penalized linear models, generalized linear models, boosted regression trees, random forests, and neural networks, that investors can deploy to forecast the cross-section of stock returns. Gaining more widespread use in economics, machine learning algorithms have demonstrated the ability to reveal complex, nonlinear patterns that are difficult or largely impossible to

Deus ex Machina A Framework for Macro Forecasting with Machine Learning

Deus ex Machina  A Framework for Macro Forecasting with Machine Learning
  • Author : Marijn A. Bolhuis,Brett Rayner
  • Publisher : International Monetary Fund
  • Release : 28 February 2020
GET THIS BOOK Deus ex Machina A Framework for Macro Forecasting with Machine Learning

We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast errors than traditional models. By combining multiple machine learning models into ensembles, we lower forecast errors even further. We also identify measures of variable importance to help improve the transparency of machine learning-based forecasts. Applying the framework to

Advanced Topics in Artificial Intelligence

Advanced Topics in Artificial Intelligence
  • Author : Australian Joint Conference on Artificial Intelligence 1999
  • Publisher : Springer Science & Business Media
  • Release : 26 November 1999
GET THIS BOOK Advanced Topics in Artificial Intelligence

This book constitutes the refereed proceedings of the 12th Australian Joint Conference on Artificial Intelligence, AI'99, held in Sydney, Australia in December 1999. The 39 revised full papers presented together with 15 posters were carefully reviewed and selected from more than 120 submissions. The book is divided in topical sections on machine learning, neural nets, knowledge representation, natural language processing, belief revision, adaptive algorithms, automated reasonning, neural learning, heuristics, and applications

Beyond Traditional Probabilistic Methods in Economics

Beyond Traditional Probabilistic Methods in Economics
  • Author : Vladik Kreinovich,Nguyen Ngoc Thach,Nguyen Duc Trung,Dang Van Thanh
  • Publisher : Springer
  • Release : 24 November 2018
GET THIS BOOK Beyond Traditional Probabilistic Methods in Economics

This book presents recent research on probabilistic methods in economics, from machine learning to statistical analysis. Economics is a very important – and at the same a very difficult discipline. It is not easy to predict how an economy will evolve or to identify the measures needed to make an economy prosper. One of the main reasons for this is the high level of uncertainty: different difficult-to-predict events can influence the future economic behavior. To make good predictions and reasonable recommendations,