Master Deep Time Series Forecasting with Python! Deep Time Series Forecasting with Python takes you on a gentle, fun and …
Build real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep …
Learn traditional and cutting-edge machine learning (ML) and deep learning techniques and best practices for time series forecasting, including global …
Given a series of wind speeds and directions from the port of Fremantle the aim of this monograph is to …
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, …
Build efficient forecasting models using traditional time series models and machine learning algorithms. Key Features Perform time series analysis and …
Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence …
The book is OK but it falls behind other available texts at comparable or lower prices. I agree with others …
The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time …
Use the power of pandas to solve most complex scientific computing problems with ease. Revised for pandas 1.x. Key Features …
Anders Milhøj's Practical Time Series Analysis Using SAS explains and demonstrates through examples how you can use SAS for time …
Written for those who need an introduction,Applied Time Series Analysisreviews applications of the popular econometric analysis technique across disciplines. Carefully …
Perform time series analysis and forecasting confidently with this Python code bank and reference manualKey FeaturesExplore forecasting and anomaly detection …
Perform time series analysis using KNIME Analytics Platform, covering both statistical methods and machine learning-based methodsKey FeaturesGain a solid understanding …
An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data.Analyzing …
Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications …
Markov chains have increasingly become useful way of capturing stochastic nature of many economic and financial variables. Although the hidden …
The field of statistics not only affects all areas of scientific activity, but also many other matters such as public …
Methods of nonlinear time series analysis are discussed from a dynamical systems perspective on the one hand, and from a …
This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass …
This paperback edition is a reprint of the 1991 edition. Time Series: Theory and Methods is a systematic account of …
This paperback edition is a reprint of the 1991 edition.Time Series: Theory and Methods is a systematic account of linear …
This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, …
PRACTICAL TIME SERIES FORECASTING WITH R: A HANDS-ON GUIDE, SECOND EDITION provides an applied approach to time-series forecasting. Forecasting is …
Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Applied Econometric …
Data Science students and practitioners want to find a forecast that “works” and don’t want to be constrained to a …
