#!/usr/bin/env python # coding: utf-8 #
# # # ## [mlcourse.ai](https://mlcourse.ai) – Open Machine Learning Course # Author: [Dmitry Sergeyev](https://github.com/DmitrySerg), Zeptolab. This material is subject to the terms and conditions of the [Creative Commons CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license. Free use is permitted for any non-commercial purpose. # #
Assignment #4. Spring 2019 # ##
Time series analysis # # Prior to working on the assignment, you'd better check out the corresponding course material: # - [Time series analysis with Python](https://nbviewer.jupyter.org/github/Yorko/mlcourse_open/blob/master/jupyter_english/topic09_time_series/topic9_part1_time_series_python.ipynb?flush_cache=true), the same as an interactive web-based [Kaggle Kernel](https://www.kaggle.com/kashnitsky/topic-9-part-1-time-series-analysis-in-python) # - [Predicting future with Facebook Prophet](https://nbviewer.jupyter.org/github/Yorko/mlcourse_open/blob/master/jupyter_english/topic09_time_series/topic9_part2_facebook_prophet.ipynb?flush_cache=true), the same as a [Kaggle Kernel](https://www.kaggle.com/kashnitsky/topic-9-part-2-time-series-with-facebook-prophet) # # You can also practice with demo assignments, which are simpler and already shared with solutions: # - "Time series analysis": [assignment](https://www.kaggle.com/kashnitsky/a9-demo-time-series-analysis) + [solution](https://www.kaggle.com/kashnitsky/a9-demo-time-series-analysis-solution) # # Also, checkout mlcourse.ai [video lecture](https://mlcourse.ai/lectures) on time series # # ### Your task is to: # 1. write code and perform computations in the cells below # 2. choose answers in the [webform](https://docs.google.com/forms/d/1D9tmL8O6ujxUD7orX-Iv_qCiYTjdDRW-uO84BeJniaI). Solutions will be shared only with those who've filled in this form # # ###