Crime Rate Prediction using Facebook Prophet

A Guideline to Make the Best Use of FB Prophet for Time Series Forecasting. Time series prediction is one of the must-know techniques for any data scientist.

Time series prediction is one of the must-know techniques for any data scientist. Questions like predicting the weather, product sales, customer visit in the shopping center, or amount of inventory to maintain, etc - all about time series forecasting, making it a valuable addition to a data scientist’s skillsets.

In this article, I will introduce *how to use Facebook Prophet to predict the crime rate in Chicago. *Split into 5 parts:

1. Prophet Introduction

2. EDA

3. Data processing

4. Model prediction

5. Takeaways

Let’s begin the journey.

1. Prophet Introduction

In 2017, Facebook Core Data Science Team open-sourced Prophet. As stated on its Github page, Prophet is:

• a procedure for forecasting time series data;
• based on additive models;
• fit non-linear trends with yearly, weekly, and daily seasonality, plus holiday effect.

Prophet uses a decomposable model with three main components, including trend, seasonality, and holidays, as combined below:

prophet time-series-forecasting python3 data-science data analysis

Applying the ARIMA model to forecast time series dataThe notion of stationarity of a series is important for applying statistical forecasting models since.

This tutorial was supposed to be published last week. Except I couldn’t get a working (and decent) model ready in time to write an article about it.

While LSTMs have become increasingly popular for time series analysis, they do have limitations. Long-short term memory networks (LSTMs) are now frequently used for time series analysis.

Learn the Fundamental Rule of Time Series Analysis: Stationarity is an important concept in the field of time series analysis with tremendous influence on how the data is perceived and predicted.

Implementing a Simple and Effective method for Demand Forecasting. Forecasting future demand is a fundamental business problem and any solution that is successful in tackling.