Every week, I share a data science book in my newsletter. In this week's edition, the focus was one of my favorite topics - time series forecasting 🎯. The Modern Time Series Forecasting with Python (2nd edition) by Manu Joseph and Jeffrey Tackes is a new book that focuses, as the name implies, on forecasting with Python with machine learning and deep learning models. The book covers both foundations and advanced topics in time series forecasting, such as: ✅ Working with time series data ✅ Exploratory analysis of time series data ✅ Core statistical models (ARIMA, exponential smoothing, etc.) ✅ Forecasting with regression models ✅ Feature engineering ✅ Forecasting with machine learning ✅ Ensembling and stacking methods ✅ Global forecasting models ✅ Forecasting with deep learning The book is for data scientists or data analysts who want to learn about forecasting using industry standards. Most of the topics in the book are explained from the ground up.