Update README.md

Author: joaopauloschuler

README.md

@@ -43,8 +43,9 @@ These examples show how to train a neural network for the task of [image classif
 * [Heatmap and Activation Map Examples with CIFAR-10](https://github.com/joaopauloschuler/k-neural-api/blob/master/examples/jupyter/activation_map_heatmap_with_cifar10.ipynb): this example shows how you can quickly display heatmap (CAM), activation maps and first layer filters/patterns.
 * [Saving a TensorFlow dataset into png files](https://colab.research.google.com/github/joaopauloschuler/k-neural-api/blob/master/examples/jupyter/k_cai_tfds_example.ipynb) so you can use the dataset with Keras image generator.
 
-There are also some advanced source code examples:
-* [kEffNet - parameter-efficient architecture with optimized pointwise convolutions](https://colab.research.google.com/github/joaopauloschuler/k-neural-api/blob/master/examples/jupyter/kEffNet_v1.ipynb): shows how to create and run an optimized neural architecture described in the papers [Grouped Pointwise Convolutions Significantly Reduces Parameters in EfficientNet](https://github.com/joaopauloschuler/kEffNet) and [Grouped Pointwise Convolutions Reduce Parameters in Convolutional Neural Networks](https://github.com/joaopauloschuler/kEffNetV1).
+### Advanced Image Classification Examples
+* [Grouped Pointwise Convolutions Reduce Parameters in Convolutional Neural Networks](https://github.com/joaopauloschuler/kEffNetV1).
+* [Grouped Pointwise Convolutions Significantly Reduces Parameters in EfficientNet](https://github.com/joaopauloschuler/kEffNet).
 * [Making plant disease classification noise resistant](https://github.com/joaopauloschuler/two-path-noise-lab-plant-disease).
 
 The following image shows a car (input sample), its heatmap and both added together.