EAN: 9781484259917

Bilder-Quelle: discount24.de - Sport-Freizeit

Learn the concepts of time series from traditional to bleeding-edge techniques. This book uses comprehensive examples to clearly illustrate statistical approaches and methods of analyzing time series data and its utilization in the real world. All the code is available in Jupyter notebooks. You'll begin by reviewing time series fundamentals the structure of time series data pre-processing and how to craft the features through data wrangling. Next you'll look at traditional time series techniques like ARMA SARIMAX VAR and VARMA using trending framework like StatsModels and pmdarima. The book also explains building classification models using sktime and covers advanced deep learning-based techniques like ANN CNN RNN LSTM GRU and Autoencoder to solve time series problem using Tensorflow. It concludes by explaining the popular framework fbprophet for modeling time series analysis. After reading Hands-On Time Series Analysis with Python you'll be able to apply these new techniques in industries such as oil and gas robotics manufacturing government banking retail healthcare and more. What You'll Learn: · Explains basics to advanced concepts of time series · How to design develop train and validate time-series methodologies · What are smoothing ARMA ARIMA SARIMA SRIMAX VAR VARMA techniques in time series and how to optimally tune parameters to yield best results · Learn how to leverage bleeding-edge techniques such as ANN CNN RNN LSTM GRU Autoencoder to solve both Univariate and multivariate problems by using two types of data preparation methods for time series. · Univariate and multivariate problem solving using fbprophet. Who This Book Is ForData scientists data analysts financial analysts and stock market researchers

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