Torrent details for "Vishwas B. Hands-on Time Series Analysis with Python. From Basic…" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
31.5 MB
Info Hash:
A61A6E2F211DD27D4793894FCDFB38FDDBC492F7
Added By:
Added:
April 20, 2026, 10:02 p.m.
Stats:
|
(Last updated: April 20, 2026, 10:07 p.m.)
| File | Size |
|---|---|
| Vishwas B. Time Series Forecasting Using Generative AI. Leveraging AI...2025.pdf | 14.5 MB |
| Vishwas B. Hands-on Time Series Analysis with Python. From Basics...2020.pdf | 17.0 MB |
Name
DL
Uploader
Size
S/L
Added
NOTE
SOURCE: Vishwas B. Hands-on Time Series Analysis with Python. From Basics...2020
-----------------------------------------------------------------------------------
COVER

-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format 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 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, 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 using two types of data prepration methods for time series. Univariate and multivariate problem solving using fbprophet. Who This Book Is For: Data scientists, data analysts, financial analysts, and stock market researchers
×


