Prophet is a Python time series forecast library developed by Facebook. Prophet automatically detects yearly, weekly, and daily seasonality. It can quickly decompose the trend and seasonality effects.
In this tutorial, we will make a time-series prediction of Bitcoin prices. The following topics will be covered:
👉 How to train a time series forecasting model using Prophet?
👉 How to make predictions and do time series decomposition?
👉 How to identify changing points in the trend?
👉 How to do time series cross-validation?
👉 How to evaluate time series model performance using Prophet?
⏰ Timecodes ⏰
0:00 - Intro
0:53 - Step 1: Import Libraries
1:28 - Step 2: Get Bitcoin Price Data
2:40 - Step 3: Train Test Split
3:14 - Step 4: Train Time Series Model Using Prophet
3:57 - Step 5: Use Prophet Model To Make Prediction
4:46 - Step 6: Time Series Decomposition
5:15 - Step 7: Identify Change Points
6:06 - Step 8: Cross-Validation
7:16 - Step 9: Prophet Model Performance Evaluation
9:02 - Summary
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