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Adding ToC to the time-series resources
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neomatrix369 committed Jan 9, 2020
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# Time-series

- [Introductory](#introductory)
- [Classification](#classification)
- [Feature engineering](#feature-engineering)
- [Methods: ARMA/ARIMA/SARIMA and others](#methods-armaarimasarima-and-others)
- [Non-stationary Time-series](#non-stationary-time-series)
- [Generalized Additive Models](#generalized-additive-models)
- [Courses / Tutorials / Workshops](#courses--tutorials--workshops)
- [Applied Time series](applied-time-series)
- [Gaussian process](#gaussian-process)
- [Neural Networks & Deep Learning](#neural-networks--deep-learning)
- [Forecasting](#forecasting)
- [Forecasting using Prophet](#forecasting-using-prophet)
- [Prediction](#prediction)
- [Trend estimation / trend analysis](#trend-estimation--trend-analysis)
- [Misc](#misc)
- [Contributing](#contributing)

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## Introductory

- [Step by Step guide to learn Time Series Modeling](https://www.analyticsvidhya.com/blog/2015/02/step-step-guide-learn-time-series/)
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## Feature engineering

[6 Powerful Feature Engineering Techniques For Time Series Data (using Python)](https://www.analyticsvidhya.com/blog/2019/12/6-powerful-feature-engineering-techniques-time-series/)
- [6 Powerful Feature Engineering Techniques For Time Series Data (using Python)](https://www.analyticsvidhya.com/blog/2019/12/6-powerful-feature-engineering-techniques-time-series/)

## Methods: ARMA/ARIMA/SARIMA and others

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## Non-stationary Time-series

[A Gentle Introduction to Handling a Non-Stationary Time Series in Python](https://www.analyticsvidhya.com/blog/2018/09/non-stationary-time-series-python/)
- [A Gentle Introduction to Handling a Non-Stationary Time Series in Python](https://www.analyticsvidhya.com/blog/2018/09/non-stationary-time-series-python/)

## Generalized Additive Models

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