171 results
- Go to itemThis workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used netwo…3
- Go to itemThis workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used netwo…3
- Go to itemHere we use word embedding instead of hot encoding, using a Word2Vec Learner node. The hidden layer size is set to 10, therefore …3
- Go to itemThis KNIME workflow focuses on creating a credit scoring model based on historical data. As with all data mining modeling activit…2
- Go to itemPartition numeric input data into a training, test, and validation set. Normalize the data into range [0,1]. Build a Keras autoen…2
- Go to itemThis KNIME workflow focuses on creating a credit scoring model based on historical data. As with all data mining modeling activit…2
- Go to itemThis ECG dataset is provided by Physikalisch-Technische Bundesanstalt (PTB) and is available on Kaggle (https://www.kaggle.com/sh…1
- Go to itemThis workflow uses Tensorflow2 to create and train a Unet for segmenting cell images. The trained network is used to predict the …1
- Go to itemThis workflow creates and trains a Unet for segmenting cell images. The trained network is used to predict the segmentation of un…1
- Go to itemThis workflow creates a credit scoring model based on historical data. As with all data mining modeling activities, it is unclear…1
- Go to itemThis is also the ECG dataset from Kaggle, put together from PhysioNet MIT-BIH Arrhythmia (https://www.kaggle.com/shayanfazeli/hea…1
- Go to itemUses a character level encoder-decoder network of LSTMs. The encoder network reads the input sentence character by character and …1
- Go to itemThis workfow uses a multitask neural network built using PyTorch and saved to the ONNX format to generate predictions. The networ…1
- Go to itemThis KNIME workflow focuses on creating a credit scoring model based on historical data. As with all data mining modeling activit…1
- Go to itemThis workflow trains and applies an LSTM network to predict energy demand using lagged values of a time series as input. In the E…1
- Go to itemThis workflow applies an LSTM network to predict energy demand using lagged values of a time series as input.1
- Go to itemThis workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used netwo…1