Abien Fred Agarap

cnn-svm. An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification

gru-svm. [ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

malware-classification. Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

wisconsin-breast-cancer. [ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

ecommerce-reviews-analysis. Statistical Analysis on E-Commerce Reviews, with Sentiment Classification using Bidirectional Recurrent Neural Network (RNN)

dl-relu. Deep Learning using Rectified Linear Units (ReLU)

pt-clustering-ae. Code implementation for "Improving k-Means Clustering Performance with Disentangled Internal Representations" by Agarap & Azcarraga (2020)

support-vector-machine. An implementation of the L2-SVM for breast cancer detection using the Wisconsin diagnostic dataset.

opencv-python-training. OpenCV-Python Tutorials

feed-forward-neural-network. An implementation of the Multilayer Perceptron for breast cancer detection using the Wisconsin diagnostic dataset.

pt-datasets. PyTorch dataset loader for image, text, malware, and medical classification datasets

vanishing-gradients. Avoiding the vanishing gradients problem by adding random noise and batch normalization

ag-news-ae-clustering. Using an Autoencoder to encode features for k-Means Clustering on the AG News Dataset

dnn-trust. How can I trust you? An intuition and tutorial on trust score

autoencoders. Jupyter Notebook

cooperative-competitive-learning. Potentially helpful methods for specialized ensemble learning.