# Hands-On Tutorial: Deep Learning for Time Series[¶](https://knowledge.dataiku.com/latest/courses/advanced-analytics/time-series-code/introduction.html#hands-on-tutorial-deep-learning-for-time-series "Permalink to this headline")

As an alternative to traditional time series models like ARIMA, you can use deep learning for forecasting.

## Objectives[¶](https://knowledge.dataiku.com/latest/courses/advanced-analytics/time-series-code/introduction.html#objectives "Permalink to this headline")

This how-to walks through how to build a long short-term memory (LSTM) network, using Keras code in Dataiku’s Visual Machine Learning.

## Prerequisites[¶](https://knowledge.dataiku.com/latest/courses/advanced-analytics/time-series-code/introduction.html#prerequisites "Permalink to this headline")

You should have some experience with Deep Learning with code in Dataiku.

You should have some familiarity with Keras.

You will need access to a code environment with the necessary libraries. When creating a code environment, you can add sets of packages on the **Packages to Install** tab. Choose the Visual Deep Learning package set that corresponds to the hardware you’re running on.
