Cover all the machine learning techniques relevant for forecasting problems ranging from
univariate and multivariate time series to supervised learning to state-of-the-art deep
forecasting models such as LSTMs recurrent neural networks Facebook's open-source Prophet
model and Amazon's DeepAR model. Rather than focus on a specific set of models this book
presents an exhaustive overview of all the techniques relevant to practitioners of forecasting.
It begins by explaining the different categories of models that are relevant for forecasting in
a high-level language. Next it covers univariate and multivariate time series models followed
by advanced machine learning and deep learning models. It concludes with reflections on model
selection such as benchmark scores vs. understandability of models vs. compute time and
automated retraining and updating of models. Each of the models presented in this book is
covered in depth with an intuitive simple explanation of the model a mathematical
transcription of the idea and Python code that applies the model to an example data set.
Reading this book will add a competitive edge to your current forecasting skillset. The book is
also adapted to those who have recently started working on forecasting tasks and are looking
for an exhaustive book that allows them to start with traditional models and gradually move
into more and more advanced models. What You Will Learn Carry out forecasting with Python
Mathematically and intuitively understand traditional forecasting models and state-of-the-art
machine learning techniques Gain the basics of forecasting and machine learning including
evaluation of models cross-validation and back testing Select the right model for the right
use case Who This Book Is For The advanced nature of the later chapters makes the book relevant
for applied experts working in the domain of forecasting as the models covered have been
published only recently. Experts working in the domain will want to update their skills as
traditional models are regularly being outperformed by newer models.
