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Match the right Time Series Forecasting Methods to the right Business Problems

There are various methods to forecast stock price, demand etc. which method/technique to be used when and how to apply the forecasting methods.

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What will you learn

  • Understanding the importance of time series
  • Understanding the mathematics of time series
  • Discussion about methods/techniques
  • Application of the models using R or Python
  • Making conclusions

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.


  • Jupyter Notebook from Anaconda installation
  • R (3.3.3) and R-Studio (1.4) installation
  • At least 4 GB RAM Machine

Project Description

In this hackerday, we will be taking open source data that are publicly available and will be discussing various methods/techniques of performing time series forecasting. We will be talking about the traditional methods such as holt-winters method, Autoregressive integrated moving average method, exponential smoothing methods, as well as we will be comparing the modern methods of performing forecasting using neural network based models.