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Titlebook: Econometrics and Data Science; Apply Data Science T Tshepo Chris Nokeri Book 2022 Tshepo Chris Nokeri 2022 Data Science.Econometrics.Machin

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發(fā)表于 2025-3-21 19:18:04 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Econometrics and Data Science
副標題Apply Data Science T
編輯Tshepo Chris Nokeri
視頻videohttp://file.papertrans.cn/302/301461/301461.mp4
概述Simplifies the economic research process from data acquisition to model development and performance evaluation.Introduces the use of mediating variables and ways of creating models that study multiple
圖書封面Titlebook: Econometrics and Data Science; Apply Data Science T Tshepo Chris Nokeri Book 2022 Tshepo Chris Nokeri 2022 Data Science.Econometrics.Machin
描述Get up to speed on the application of machine learning approaches in macroeconomic research. This book brings together economics and data science..Author Tshepo Chris Nokeri begins by introducing you to covariance analysis, correlation analysis, cross-validation, hyperparameter optimization, regression?analysis, and residual analysis. In addition, he presents an approach to contend with multi-collinearity. He then debunks a time series model recognized as the additive model. He reveals a technique for binarizing an economic feature to perform classification analysis using logistic regression. He brings in the Hidden Markov Model, used to discover hidden patterns and growth in the world economy. The author demonstrates unsupervised machine learning techniques such as principal component analysis and?cluster analysis. Key deep learning concepts and ways of?structuring artificial neural networks are explored along with training them and assessing their performance. The Monte Carlo simulation technique is applied to stimulate the purchasing power of money in an?economy. Lastly, the Structural Equation Model (SEM) is considered to integrate correlation analysis, factor analysis, multiva
出版日期Book 2022
關(guān)鍵詞Data Science; Econometrics; Machine learning; Statistics; Deep Learning; Neural Networks; Time Series Anal
版次1
doihttps://doi.org/10.1007/978-1-4842-7434-7
isbn_softcover978-1-4842-7433-0
isbn_ebook978-1-4842-7434-7
copyrightTshepo Chris Nokeri 2022
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沙發(fā)
發(fā)表于 2025-3-21 23:37:26 | 只看該作者
板凳
發(fā)表于 2025-3-22 01:30:27 | 只看該作者
https://doi.org/10.1007/978-1-4842-7434-7Data Science; Econometrics; Machine learning; Statistics; Deep Learning; Neural Networks; Time Series Anal
地板
發(fā)表于 2025-3-22 06:30:26 | 只看該作者
978-1-4842-7433-0Tshepo Chris Nokeri 2022
5#
發(fā)表于 2025-3-22 10:43:39 | 只看該作者
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發(fā)表于 2025-3-22 16:51:57 | 只看該作者
Inflation Simulation, Carlo simulation model. In particular, it employs this model to determine the probability of a change in the country’s central government debt across multiple trials. This method is useful when handling sequential data.
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發(fā)表于 2025-3-22 19:28:24 | 只看該作者
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發(fā)表于 2025-3-23 04:53:31 | 只看該作者
Asian/American Curricular Epistemicideds, which paves the way for the econometrics field. It also covers the relevance of econometrics in devising and revising the economic policies of a nation. It then summarizes machine learning, deep learning, and structural equation modeling. To conclude, it reveals ways to extract macroeconomic data using a standard Python library.
10#
發(fā)表于 2025-3-23 08:58:53 | 只看該作者
https://doi.org/10.1007/978-3-662-05850-3 Carlo simulation model. In particular, it employs this model to determine the probability of a change in the country’s central government debt across multiple trials. This method is useful when handling sequential data.
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