Pinned Repositories
ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
anomaly_detection
This is the official implementation of "Anomaly Detection with Deep Perceptual Autoencoders".
Anomaly_Detection_NN
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Deep_Learning_Autonomous_Vehicle
Earley_Python
final
keras-yolo3
A Keras implementation of YOLOv3 (Tensorflow backend)
SUMO-Unity3D-connection
This example demonstrates real-time communication between the microscopic traffic simulator SUMO and the 3D game engine Unity 3D with Python 3.7 based TCP/IP server. Video about the example: https://www.youtube.com/watch?v=4RiJyDnm41Q
kafee23's Repositories
kafee23/Anomaly_Detection_NN
kafee23/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
kafee23/keras-yolo3
A Keras implementation of YOLOv3 (Tensorflow backend)
kafee23/ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
kafee23/anomaly_detection
This is the official implementation of "Anomaly Detection with Deep Perceptual Autoencoders".
kafee23/Deep_Learning_Autonomous_Vehicle
kafee23/Earley_Python
kafee23/final
kafee23/SUMO-Unity3D-connection
This example demonstrates real-time communication between the microscopic traffic simulator SUMO and the 3D game engine Unity 3D with Python 3.7 based TCP/IP server. Video about the example: https://www.youtube.com/watch?v=4RiJyDnm41Q