Deep Learning for Time Series and why DEEP LEARNING?

Neural networks have proven their abilities to learn complex mappings many times in the past. Deep learning neural networks can be a powerful tool to predict the future due to its nature of discovering complex nonlinear dependencies. Time Series Forecasting problems are one of the most difficult problems in real life as there are many unpredictables resulting in complex temporal dependences. For instance, stock prices can form very nice time series; yet there are still no good ways to predict the stock prices even with the newest technology/algorithms. To deal with that, when it comes to modeling, we have to add in additional structures to improve the performance of the model.