Tag: Forecasting

Ultimate Enterprise Data Analysis and Forecasting using Python Leverage Cloud platforms with Azure Time Series Insights


Free Download Ultimate Enterprise Data Analysis and Forecasting Using Python: Leverage Cloud Platforms with Azure Time Series Insights and AWS Forecast Components for Deep Learning Modeling Using Python (English Edition)
by Pandian, Shanthababu;

English | 2023 | ISBN: 8119416449 | 442 pages | True/Retail EPUB | 14.88 MB

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Recent Advances in Modeling and Forecasting Kaiyu (2024)


Free Download Recent Advances in Modeling and Forecasting Kaiyu: Tools for Predicting and Verifying the Effects of Urban Revitalization Policy by Saburo Saito, Kenichi Ishibashi, Kosuke Yamashiro
English | EPUB (True) | 2023 | 620 Pages | ISBN : 9819912407 | 101.6 MB
This book is the first comprehensive presentation of a Kaiyu Markov model with covariates and a multivariate Poisson model with competitive destinations. These two models are core techniques when the authors and colleagues conduct their Kaiyu studies. The two models are usually used to forecast the effects of specific urban redevelopment on both the number of visitors and consumer shop-around or Kaiyu movements. Their Kaiyu studies originated from the constructions of a Kaiyu Markov model and the disaggregated hierarchical decision Huff model almost simultaneously around the early 1980s. This book retrospectively reviews how these models have evolved from the start to the present state, and previews the ongoing efforts to make further extensions of these models. The extension of the Huff model started from the disaggregated hierarchical decision Huff model with shop-arounds. In retrospect, the model formulated the consumer’s simultaneous choice of destinations as a joint probability. The mechanism to determine this joint probability was a recursive conditional probability system. Now the Huff model has shifted from joint probability to multivariate frequency Poisson with competitive destinations. On the other hand, the Kaiyu Markov model started from a descriptive model. Because it cannot forecast changes in shop-arounds or consumer Kaiyu behaviors, the Kaiyu Markov model with covariates was developed in which entrance and shop-around choice probabilities are explained by the respective two logit models with covariates such as distances and shop-floor areas. The noticeable point is that it can explain consumers’ probability of quitting their shop-arounds. Thus, the model enables one to evaluate the effects of urban revitalization policy that promotes consumers’ shop-arounds or Kaiyu behaviors. Furthermore, if the Kaiyu Markov model can estimate the actual numbers of flows of consumers’ shop-arounds among shopping sites, the corresponding money flows also can be estimated as economic effects. This book discusses from scratch the evolution of all these topics. Thus this book provides the basics of the Kaiyu Markov model, a tutorial for the theory and estimation of the conditional logit model, and a chapter serving as a practical research manual for forecasting changes caused by urban development based on consumers’ Kaiyu behaviors.

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Wind Power Analysis And Forecasting Using Machine Learning With Python


Free Download Wind Power Analysis And Forecasting Using Machine Learning With Python by Vivian Siahaan
English | May 18, 2022 | ISBN: B0B1Q4LP6Q | 215 pages | MOBI | 18 Mb
In this project on wind power analysis and forecasting using machine learning with Python, we started by exploring the dataset. We examined the available features and the target variable, which is the active power generated by wind turbines. The dataset likely contained information about various meteorological parameters and the corresponding active power measurements.

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TIME-SERIES WEATHER FORECASTING AND PREDICTION WITH PYTHON


Free Download TIME-SERIES WEATHER: FORECASTING AND PREDICTION WITH PYTHON by Vivian Siahaan, Rismon Hasiholan Sianipar
English | February 18, 2022 | ISBN: N/A | ASIN: B09SWCB1TZ | 302 pages | MOBI | 25 Mb
In this project, we embarked on a journey of exploring time-series weather data and performing forecasting and prediction using Python. The objective was to gain insights into the dataset, visualize feature distributions, analyze year-wise and month-wise patterns, apply ARIMA regression to forecast temperature, and utilize machine learning models to predict weather conditions. Let’s delve into each step of the process.

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Modern Time Series Forecasting with Python


Free Download Modern Time Series Forecasting with Python: Explore industry-ready time series forecasting using modern machine learning and deep learning by Manu Joseph
English | November 24, 2022 | ISBN: 1803246804 | 552 pages | PDF | 25 Mb
Build real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep learning concepts

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CRYPTOCURRENCY PRICE ANALYSIS, PREDICTION, AND FORECASTING USING MACHINE LEARNING WITH PYTHON


Free Download CRYPTOCURRENCY PRICE ANALYSIS, PREDICTION, AND FORECASTING USING MACHINE LEARNING WITH PYTHON by Vivian Siahaan, Rismon Hasiholan Sianipar
English | May 28, 2022 | ISBN: N/A | ASIN: B0B2MT6V71 | 476 pages | PDF | 15 Mb
In this project, we will be conducting a comprehensive analysis, prediction, and forecasting of cryptocurrency prices using machine learning with Python. The dataset we will be working with contains historical cryptocurrency price data, and our main objective is to build models that can accurately predict future price movements and daily returns.

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Ultimate Enterprise Data Analysis and Forecasting using Python


Free Download Ultimate Enterprise Data Analysis and Forecasting using Python
English | 2023 | ISBN: 8119416449 | 442 Pages | EPUB (True) | 18 MB
Embark on a transformative journey through the intricacies of time series analysis and forecasting with this comprehensive handbook. Beginning with the essential packages for data science and machine learning projects you will delve into Python’s prowess for efficient time series data analysis, exploring the core components and real-world applications across various industries through compelling use-case studies. From understanding classical models like AR, MA, ARMA, and ARIMA to exploring advanced techniques such as exponential smoothing and ETS methods, this guide ensures a deep understanding of the subject.

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Solar Irradiance and Photovoltaic Power Forecasting


Free Download Solar Irradiance and Photovoltaic Power Forecasting
English | 2024 | ISBN: 1032068124 | 682 Pages | PDF (True) | 31 MB
Forecasting plays an indispensable role in grid integration of solar energy, which is an important pathway toward the grand goal of achieving planetary carbon neutrality. This rather specialized field of solar forecasting constitutes both irradiance and photovoltaic power forecasting. Its dependence on atmospheric sciences and implications for power system operations and planning make the multi-disciplinary nature of solar forecasting immediately obvious. Advances in solar forecasting represent a quiet revolution, as the landscape of solar forecasting research and practice has dramatically advanced as compared to just a decade ago.

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Time Series Forecasting in Python


Free Download Time Series Forecasting in Python by Marco Peixeiro
English | November 15th, 2022 | ISBN: 161729988X | 456 pages | True EPUB (Retail Copy) | 17.14 MB
Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting.

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