and when I changemodel.train_model(train_df)tomodel.train_model(pd.DataFrame(train_df.values.tolist()[:10]))it gives the error we discuss here:ValueError: too many dimensions 'str' Then, if I keep only one text column, it's fine:model.train_model(pd.DataFrame(train_df[['text_a',...
Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported,
One of the most effective approaches has been to use Deep Learning in combination with other algorithms. We have seen this in the AlphaGo implementation that used a Monte-Carlo Tree Search technique in combination with Deep Learning. The integration of a symbolic approach with Deep Learning is al...
It is evident that the lower performing models Figure 5c,d suffered primarily from low precision; the b-LSTM implementation detected 117 out of 204 events correctly, but it generated 448 spurious or fragmented events. The ms-CNN model Figure 5b demonstrates the effect of adding additional stride...
For more information, please refer to https://www.mdpi.com/openaccess. Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an ...
2.1. Transport of Colloids and Fluid A two-fluid model based on an energy landscape enables the implementation of colloid/membrane interactions in the fluid and colloids momentum and mass balances [18]. Such a Eulerian approach assumes that the fluid and the colloid phases are a continuous ...
Matlab-based deep learning toolkit that supports arbitrary directed acyclic graphs (DAG). Support DNN, LSTM, CNN layers and many signal processing layers. Include recipes/examples of using the tool for various tasks. - singaxiong/SignalGraph
Intelligent virtual machines contain some pre-trained domain models based mainly on convolutional neural network (CNN) and long short term memory (LSTM) ANNs [24,25]. Several virtual machines can run on a host, but they can migrate from the source computer to the destination regarding the Paret...