@@ -28,6 +28,7 @@ The Following list gives an overview of features and their status. Keep in meind
- Graph (very simple solution implemented)
- Transposed Convolution (implemented, works)
- LR Scheduler (implemented)
- Tensors with autograd (started)
- Random Forrest
- DecisionTree (Modular)
- Impurity Measures (Gini, Entropy, MAE, MSE)
...
...
@@ -55,6 +56,8 @@ The Following list gives an overview of features and their status. Keep in meind
- learning rate scheduler from Neural Network (works)
- calculating umatrix (implemented)
- evaluating the map (minimally implemented)
- all applications can be saved/loaded as/from json files
The network code is up and running, forward and backward propagation works with Linear, Convolution and Activation, with Dropout and Pooling should work. I am pretty sure that there a bugs and mistakes. But on simple test data it already works well.
