Machine Learning for Time Series Forecasting with Python, An Indian Adaptation
Description
Machine Learning for Time Series Forecasting with Python is full real-world examples, resources, and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. This book is perfect for entry-level data scientists, business analysts, developers, and researchers. This book offers a comprehensive introduction to the core concepts, terminology, approaches, and applications of machine learning and deep learning for time series forecasting: understanding these principles leads to more flexible and successful time series applications.
Apart from this, in this Indian Adaptation, you’ll get:
- New self-evaluation Multiple Choice, Review, and Job-Interview Questions to equip the knowledge and confidence to excel in interviews
- India-specific case studies, Time Series Forecasting for Demand Planning at Flipkart and Predictive Maintenance at Tata Steel.
- Appendix on “Enhancing Time Series Forecasting for the Indian Market”
Table of Contents
Acknowledgments
Introduction
Chapter 1 Overview of Time Series Forecasting
Chapter 2 How to Design an End-to-End Time Series Forecasting Solution on the Cloud
Chapter 3 Time Series Data Preparation
Chapter 4 Introduction to Autoregressive and Automated Methods for Time Series Forecasting
Chapter 5 Introduction to Neural Networks for Time Series Forecasting
Chapter 6 Model Deployment for Time Series Forecasting
Case Study 1 Time Series Forecasting for Demand Planning at Flipkart
Case Study 2 Predictive Maintenance at Tata Steel
Appendix A Enhancing Time Series Forecasting for the Indian Market
Appendix B Questions
References
Index