Table of Contents

14 Chapters · 25 Lessons

    1. Ultimate Enterprise Data Analysis and Forecasting using Python Free preview

    1. (Included in full purchase)

      Introduction

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      Introduction to Python and its key packages for DS and ML Projects

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      Introduction to Python and its key packages for DS and ML Projects

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      Python for Time Series Data Analysis

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      Python for Time Series Data Analysis

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      Time Series Analysis and its Components

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      Time Series Analysis and its Components

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      Time Series Analysis and Forecasting Opportunities in Various Industries

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      Time Series Analysis and Forecasting Opportunities in Various Industries

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      Exploring various aspects of Time Series Analysis and Forecasting

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      Exploring various aspects of Time Series Analysis and Forecasting

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      Exploring Time Series Models - AR, MA, ARMA, and ARIMA

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      Exploring Time Series Models - AR, MA, ARMA, and ARIMA

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      Understanding Exponential Smoothing and ETS Methods in TSA

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      Understanding Exponential Smoothing and ETS Methods in TSA

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      Exploring Vector Autoregression and its Subsets(VAR, VMA, and VARMA)

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      Exploring Vector Autoregression and its Subsets(VAR, VMA, and VARMA)

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      Deep Learning for Time Series Analysis and Forecasting

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      Deep Learning for Time Series Analysis and Forecasting

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      Azure Time Series Insights

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      Azure Time Series Insights

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      AWS Forecast

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      AWS Forecast

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      Index

About the Book

Embark on a transformative journey through the intricacies of time series analysis and forecasting with this comprehensive handbook. Beginning with the essential packages for data science and machine learning projects you will delve into Python's prowess for efficient time series data analysis, exploring the core components and real-world applications across various industries through compelling use-case studies. From understanding classical models like AR, MA, ARMA, and ARIMA to exploring advanced techniques such as exponential smoothing and ETS methods, this guide ensures a deep understanding of the subject. It will help you navigate the complexities of vector autoregression (VAR, VMA, VARMA) and elevate your skills with a deep dive into deep learning techniques for time series analysis. By the end of this book, you will be able to harness the capabilities of Azure Time Series Insights and explore the cutting-edge AWS Forecast components, unlocking the cloud's power for advanced and scalable time series forecasting.

About the Author

Shanthababu Pandian holds a Bachelor’s degree in engineering in Electronics and Communication, followed by three Master's degrees - MTech, MBA, and M.S. - from a prestigious university in India. Additionally, he completed a Post Graduate Program in Artificial Intelligence and Machine Learning from the University of Texas, along with a Post Graduate Certification in Data Science from the Indian Institute of Technology, Guwahati. With over 21 years of extensive experience in information technology (IT), Shanthababu specializes in data engineering and analytics solutions, development and implementation using agile methodologies, and building complex data models for Business Intelligence (BI) and data science products for various customers located across the UK and US regions.