I thought this was Renee's website! (Maybe hers is becomingdatascience.com?) Most machine learning (ML) models use samples / examples observations as input. This data lacks any time dimension. Time-series forecasting models are...
Traditionally most machine learning (ML) models use as input features some observations (samples / examples) but there is no time dimension in the data. Time-series forecasting models are the models…
Jeremy is talking about that CNN maybe will take over by the end of the year. What would be the best solution for a time series with parallel parameters that normally use LSTM/GRU to solve before? For example predicting…
LSTM-Human-Activity-Recognition - Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).
Y. Kim, K. Stratos, and D. Kim. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), page 643--653. Vancouver, Canada, Association for Computational Linguistics, (July 2017)