|
@@ -316,7 +316,7 @@
|
|
|
28. [Machine Learning Mastery blog](https://machinelearningmastery.com/blog/)
|
|
|
29. [ML Compiled](https://ml-compiled.readthedocs.io/en/latest/)
|
|
|
30. [Programming Community Curated Resources](https://hackr.io/tutorials/learn-artificial-intelligence-ai)
|
|
|
-28. [A Beginner's Guide To Understanding Convolutional Neural Networks](https://adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/)
|
|
|
+31. [A Beginner's Guide To Understanding Convolutional Neural Networks](https://adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/)
|
|
|
|
|
|
### Datasets
|
|
|
|
|
@@ -570,6 +570,8 @@
|
|
|
36. [Awesome Network Embedding](https://github.com/chihming/awesome-network-embedding) - Curated list of articles related to deep learning scientific research on graph structured data at the node level.
|
|
|
37. [Microsoft Recommenders](https://github.com/Microsoft/Recommenders) contains examples, utilities and best practices for building recommendation systems. Implementations of several state-of-the-art algorithms are provided for self-study and customization in your own applications.
|
|
|
38. [The Unreasonable Effectiveness of Recurrent Neural Networks](http://karpathy.github.io/2015/05/21/rnn-effectiveness/) - Andrej Karpathy blog post about using RNN for generating text.
|
|
|
+39. [Ladder Network](https://github.com/divamgupta/ladder_network_keras) - Keras Implementation of Ladder Network for Semi-Supervised Learning
|
|
|
+
|
|
|
|
|
|
-----
|
|
|
### Contributing
|