Forecasting 📈 is perhaps the most common application of machine learning in the real world. Time series forecasting is a broad field with a long history. This course focuses on the application of modern machine learning methods to time series data with the goal of producing the most accurate predictions. The lessons in this course were inspired by winning solutions from past Kaggle forecasting competitions but will be applicable whenever accurate forecasts are a priority.

After finishing this course, you'll know how to:

• Engineer features to model the major time series components (trends, seasons, and cycles),
• Visualize time series with many kinds of time series plots,
• Create forecasting hybrids that combine the strengths of complementary models, and
• Adapt machine learning methods to a variety of forecasting tasks.

As part of the exercises, you'll get a chance to participate in our Store Sales - Time Series Forecasting Getting Started competition. In this competition, you're tasked with forecasting sales for Corporación Favorita (a large Ecuadorian-based grocery retailer) in almost 1800 product categories.

To check the learning material in advance, check Kaggle's microcourse 👇 :

https://www.kaggle.com/learn/time-series

Let's get started!

Prerequisites:

1. Have access to a Browser (preferably Google Chrome)

2. Sign up to Kaggle

3. Eager to Learn !!!

4.Have Completed the courses:

• "Intro to Machine Learning"
• "Intermediate Machine Learning"
• "Intro to Deep Learning"