DDE-2/Basics-of-CNN.md

@@ -8,7 +8,7 @@ _C. Ates_
 
 ## Basics of CNNs
 
--[An introduction to Convolutional Neural Networks](https://towardsdatascience.com/an-introduction-to-convolutional-neural-networks-eb0b60b58fd7)
+- [An introduction to Convolutional Neural Networks](https://towardsdatascience.com/an-introduction-to-convolutional-neural-networks-eb0b60b58fd7)
 
 - [A Survey of the Recent Architectures of Deep Convolutional Neural Networks](https://arxiv.org/ftp/arxiv/papers/1901/1901.06032.pdf)
 
@@ -19,21 +19,21 @@ _C. Ates_
 
 ## Convolutional Autoencoders
 
--[Convolutional Autoencoders (CAE) with Tensorflow](https://ai.plainenglish.io/convolutional-autoencoders-cae-with-tensorflow-97e8d8859cbe)
+- [Convolutional Autoencoders (CAE) with Tensorflow](https://ai.plainenglish.io/convolutional-autoencoders-cae-with-tensorflow-97e8d8859cbe)
 
 - [Image Noise Reduction I](https://towardsdatascience.com/convolutional-autoencoders-for-image-noise-reduction-32fce9fc1763)
 
 - [Keras - image denoising](https://keras.io/examples/vision/autoencoder/)
 
--[Pre-Training CNNs Using Convolutional Autoencoders](https://www.ni.tu-berlin.de/fileadmin/fg215/teaching/nnproject/cnn_pre_trainin_paper.pdf)
+- [Pre-Training CNNs Using Convolutional Autoencoders](https://www.ni.tu-berlin.de/fileadmin/fg215/teaching/nnproject/cnn_pre_trainin_paper.pdf)
 
 ## Famous CNN Architectures 
 
 - [CNN Literature](https://paperswithcode.com/methods/category/convolutional-neural-networks)
 
--[Illustrated: 10 CNN Architectures I](https://towardsdatascience.com/illustrated-10-cnn-architectures-95d78ace614d)
+- [Illustrated: 10 CNN Architectures I](https://towardsdatascience.com/illustrated-10-cnn-architectures-95d78ace614d)
 
--[Illustrated: 10 CNN Architectures II](https://towardsdatascience.com/top-10-cnn-architectures-every-machine-learning-engineer-should-know-68e2b0e07201)
+- [Illustrated: 10 CNN Architectures II](https://towardsdatascience.com/top-10-cnn-architectures-every-machine-learning-engineer-should-know-68e2b0e07201)
 
 - [AlexNet to EfficientNet](https://theaisummer.com/cnn-architectures/)