Hands-on Time Series Analysis with Python: From Basics to Bleeding Edge Techniques
By 作者:B V Vishwas and ASHISH PATEL
Paperback : 428 pages
ISBN-10 : 1484259912
ISBN-13 : 9781484259917
Product Dimensions : 15.49 x 2.46 x 23.5 cm
Publisher Finelybook 出版社 : Apress; 1st ed. Edition (25 Aug. 2020)
Language 语言: : English
The Book Description robot was collected from Amazon and arranged by Finelybook
Learn the concepts of time series from traditional to leading-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 作者: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 作者: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, test 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 作者:using two types of data prepration methods for time series.
Univariate and multivariate problem solving using fbprophet.