Added Graph Representation learning and awesome

Added section about graph representation learning and 6 Awesome Repos.

Author: benedekrozemberczki

README.md

@@ -523,7 +523,12 @@ Plotting learning curve: [link](http://www.ritchieng.com/machinelearning-learnin
 [autokeras](https://github.com/jhfjhfj1/autokeras) - AutoML for deep learning.  
 [nni](https://github.com/Microsoft/nni) - Toolkit for neural architecture search and hyper-parameter tuning by Microsoft.  
 [automl-gs](https://github.com/minimaxir/automl-gs) - Automated machine learning.  
-[mljar](https://github.com/mljar/mljar-supervised) - Automated machine learning.  
+[mljar](https://github.com/mljar/mljar-supervised) - Automated machine learning.
+
+#### Graph Representation Learning
+[Karate Club](https://github.com/rusty1s/pytorch_geometric) - Unsupervised learning on graphs.
+[Pytorch Geometric](https://github.com/benedekrozemberczki/karateclub) - Graph representation learning with PyTorch.
+[DLG](https://github.com/dmlc/dgl) - Graph representation learning with TensorFlow.
 
 #### Evolutionary Algorithms & Optimization
 [deap](https://github.com/DEAP/deap) - Evolutionary computation framework (Genetic Algorithm, Evolution strategies).  
@@ -622,17 +627,23 @@ Gilbert Strang - [Matrix Methods in Data Analysis, Signal Processing, and Machin
 [Awesome AI on Kubernetes](https://github.com/CognonicLabs/awesome-AI-kubernetes)  
 [Awesome Big Data](https://github.com/onurakpolat/awesome-bigdata)  
 [Awesome Business Machine Learning](https://github.com/firmai/business-machine-learning)  
-[Awesome Causality](https://github.com/rguo12/awesome-causality-algorithms)  
-[Awesome CSV](https://github.com/secretGeek/AwesomeCSV)  
+[Awesome Causality](https://github.com/rguo12/awesome-causality-algorithms)
+[Awesome Community Detection](https://github.com/benedekrozemberczki/awesome-community-detection)
+[Awesome CSV](https://github.com/secretGeek/AwesomeCSV)
 [Awesome Data Science with Ruby](https://github.com/arbox/data-science-with-ruby)  
 [Awesome Dash](https://github.com/ucg8j/awesome-dash)  
-[Awesome Deep Learning](https://github.com/ChristosChristofidis/awesome-deep-learning)  
+[Awesome Decision Trees](https://github.com/benedekrozemberczki/awesome-decision-tree-papers)
+[Awesome Deep Learning](https://github.com/ChristosChristofidis/awesome-deep-learning)
 [Awesome ETL](https://github.com/pawl/awesome-etl)  
-[Awesome Financial Machine Learning](https://github.com/firmai/financial-machine-learning)  
-[Awesome GAN Applications](https://github.com/nashory/gans-awesome-applications)  
+[Awesome Financial Machine Learning](https://github.com/firmai/financial-machine-learning)
+[Awesome Fraud Detection](https://github.com/benedekrozemberczki/awesome-fraud-detection-papers)
+[Awesome GAN Applications](https://github.com/nashory/gans-awesome-applications)
+[Awesome Graph Classification](https://github.com/benedekrozemberczki/awesome-graph-classification)
+[Awesome Gradient Boosting](https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers)
 [Awesome Machine Learning](https://github.com/josephmisiti/awesome-machine-learning#python)  
 [Awesome Machine Learning Interpretability](https://github.com/jphall663/awesome-machine-learning-interpretability)   
-[Awesome Machine Learning Operations](https://github.com/EthicalML/awesome-machine-learning-operations)  
+[Awesome Machine Learning Operations](https://github.com/EthicalML/awesome-machine-learning-operations)
+[Awesome Monte Carlo Tree Search](https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers)
 [Awesome Online Machine Learning](https://github.com/MaxHalford/awesome-online-machine-learning)  
 [Awesome Python](https://github.com/vinta/awesome-python)   
 [Awesome Python Data Science](https://github.com/krzjoa/awesome-python-datascience)