In this chapter, we have described three deep learning-based approaches to develop time series forecasting models. Neural networks are suitable in cases where there is little information about the underlying properties such as long-term trend and seasonality or these are too complex to be modeled with an acceptable degree of accuracy by traditional statistical methods. Different neural network architectures such as MLP, RNN, and CNN extract complex patterns from the data. If neural network models are trained with appropriate measures to avoid overfitting on training data, then these models generalize well on unseen validation or test data. To avoid overfitting, we applied dropout, which is widely used in deep neural networks for a variety of datasets and applications. We hope that this chapter gives you an idea of advanced techniques available for time series forecasting. The Jupyter notebooks accompanying the chapter are expected to give you the necessary base knowledge, which would...
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Dr. Avishek Pal, PhD, is a software engineer, data scientist, author, and an avid Kaggler living in Hyderabad, India. He achieved his Bachelor of Technology degree in industrial engineering from the Indian Institute of Technology (IIT) Kharagpur and earned his doctorate in 2015 from University of Warwick, Coventry, United Kingdom. He started his career as a software engineer at IBM India developing middleware solutions for telecom clients. This was followed by stints at a start-up product development company followed by Ericsson, the global telecom giant. After doctoral studies, Avishek started his career in India as a lead machine learning engineer for a leading US-based investment company. He is currently working at Microsoft as a senior data scientist. Avishek has published several research papers in reputed international conferences and journals.
Read more about Avishek Pal
Dr. PKS Prakash is a data scientist and author. He has spent the last 12 years in developing many data science solutions in several practical areas in healthcare, manufacturing, pharmaceuticals, and e-commerce. He currently works as the data science manager at ZS Associates. He is the co-founder of Warwick Analytics, a spin-off from University of Warwick, UK. Prakash has published articles widely in research areas of operational research and management, soft computing tools, and advanced algorithms in leading journals such as IEEE-Trans, EJOR, and IJPR, among others. He has edited an article on Intelligent Approaches to Complex Systems and contributed to books such as Evolutionary Computing in Advanced Manufacturing published by WILEY and Algorithms and Data Structures using R and R Deep Learning Cookbook, published by PACKT.
Read more about PKS Prakash
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Dr. Avishek Pal, PhD, is a software engineer, data scientist, author, and an avid Kaggler living in Hyderabad, India. He achieved his Bachelor of Technology degree in industrial engineering from the Indian Institute of Technology (IIT) Kharagpur and earned his doctorate in 2015 from University of Warwick, Coventry, United Kingdom. He started his career as a software engineer at IBM India developing middleware solutions for telecom clients. This was followed by stints at a start-up product development company followed by Ericsson, the global telecom giant. After doctoral studies, Avishek started his career in India as a lead machine learning engineer for a leading US-based investment company. He is currently working at Microsoft as a senior data scientist. Avishek has published several research papers in reputed international conferences and journals.
Read more about Avishek Pal
Dr. PKS Prakash is a data scientist and author. He has spent the last 12 years in developing many data science solutions in several practical areas in healthcare, manufacturing, pharmaceuticals, and e-commerce. He currently works as the data science manager at ZS Associates. He is the co-founder of Warwick Analytics, a spin-off from University of Warwick, UK. Prakash has published articles widely in research areas of operational research and management, soft computing tools, and advanced algorithms in leading journals such as IEEE-Trans, EJOR, and IJPR, among others. He has edited an article on Intelligent Approaches to Complex Systems and contributed to books such as Evolutionary Computing in Advanced Manufacturing published by WILEY and Algorithms and Data Structures using R and R Deep Learning Cookbook, published by PACKT.
Read more about PKS Prakash