Vishwas B Hands-on Time Series Analysis with Python From Basics 2020
Category: eBooks
- views: 111
- date: 25 March 2025
- posted by: BeMyLove

Vishwas B Hands-on Time Series Analysis with Python From Basics 2020 | 31.49 MB
Title: Hands-on Time Series Analysis with Python: From Basics to Bleeding Edge Techniques
Author: Vishwas
Description:
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 For Data scientists, data analysts, financial analysts, and stock market researchers
DOWNLOAD:
https://rapidgator.net/file/37ea3a865daf12aa647095422a76d201/Vishwas_B._Hands-on_Time_Series_Analysis_with_Python._From_Basics...2020.rar
https://nitroflare.com/view/A7F296CF9C36588/Vishwas_B._Hands-on_Time_Series_Analysis_with_Python._From_Basics...2020.rar
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 For Data scientists, data analysts, financial analysts, and stock market researchers
DOWNLOAD:
https://rapidgator.net/file/37ea3a865daf12aa647095422a76d201/Vishwas_B._Hands-on_Time_Series_Analysis_with_Python._From_Basics...2020.rar
https://nitroflare.com/view/A7F296CF9C36588/Vishwas_B._Hands-on_Time_Series_Analysis_with_Python._From_Basics...2020.rar
We need your support!
Make a donation to help us stay online
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem
Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u
USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm
Information |
|||
![]() |
Users of GUESTS are not allowed to comment this publication. | ||









