Time series classification with Tensorflow

Time-series data arise in many fields including finance, signal processing, speech recognition and medicine. A standard approach to time-series problems usually requires manual engineering of features which can then be fed into a machine learning algorithm. Engineering of features generally requires some domain knowledge of the discipline where the data has originated from. For example, if one is dealing with signals (i.e. A similar situation arises in image classification, where manually engineered features (obtained by applying a number of filters) could be used in classification algorithms.