Advanced forecasting with Python : with state-of-the-art-models including LSTMs, Facebook's Prophet, and Amazon's DeepAR (Record no. 661986)
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000 -LEADER | |
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fixed length control field | 01650nam a22001817a 4500 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9781484283400 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Edition number | 1 |
Classification number | 005.133 |
Item number | KOR-A |
100 ## - MAIN ENTRY--AUTHOR NAME | |
Personal name | Korstanje, Joos |
245 ## - TITLE STATEMENT | |
Title | Advanced forecasting with Python : with state-of-the-art-models including LSTMs, Facebook's Prophet, and Amazon's DeepAR |
Statement of responsibility, etc | By Joos Korstanje |
250 ## - EDITION STATEMENT | |
Edition statement | 1 |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Name of publisher | Apress, |
Year of publication | c2021. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | i-xvii+296P. |
505 ## - FORMATTED CONTENTS NOTE | |
Formatted contents note | Chapter 1: Models for Forecasting<br/>Chapter 2: Model Evaluation for Forecasting<br/>Chapter 3: The AR Model<br/>Chapter 4: The MA model<br/>Chapter 5: The ARMA model<br/>Chapter 6: The ARIMA model<br/>Chapter 7: The SARIMA Model<br/>Chapter 8: The VAR model<br/>Chapter 9: The Bayesian VAR model<br/>Chapter 10: The Linear Regression model<br/>Chapter 11: The Decision Tree model<br/>Chapter 12: The k-Nearest Neighbors VAR model<br/>Chapter 13: The Random Forest Model<br/>Chapter 14: The XGBoost model<br/>Chapter 15: The Neural Network model<br/>Chapter 16: Recurrent Neural Networks<br/>Chapter 17: LSTMs<br/>Chapter 18: Facebook's Prophet model<br/>Chapter 19: Amazon's DeepAR Model<br/>Chapter 20: Deep State Space Models<br/>Chapter 21: Model selection |
520 ## - SUMMARY, ETC. | |
Summary, etc | :Cover all the machine learning techniques relevant for forecasting problems, ranging from univariate and multivariate time series to supervised learning, to state-of-the-art deep forecasting models such as LSTMs, recurrent neural networks, Facebook's open-source Prophet model, and Amazon's DeepAR model. Rather than focus on a specific set of models, |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical Term | Electronic books, Machine learning Python, Time-series analysis Data processing |
856 ## - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://www.worldcat.org/title/1259625412 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | Book |
Withdrawn status | Lost status | Damaged status | Not for loan | Home Library | Current Location | Date acquired | Full call number | Accession Number | Price effective from | Koha item type | Shelving location |
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Dept. of Computational Biology and Bioinformatics | Dept. of Computational Biology and Bioinformatics | 31/10/2022 | 005.133 KOR-A | DCB4167 | 31/10/2022 | Book | |||||
Dept. of Futures Studies | Dept. of Futures Studies | 19/05/2023 | 005.133 KOR | DFS4564 | 19/05/2023 | Book | General Stacks |