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1. Heart-Disease-Diagnosis-using-ML-Ensemble-Methods Heart-Disease-Diagnosis-using-ML-Ensemble-Methods Public

   The purpose of this project is to accurately diagnose heart disease using different machine learning techniques and classifiers, including ensemble methods.

   Jupyter Notebook 1 1

2. Anomaly-Detection-with-CNNs-for-Industrial-Surface-Inspection Anomaly-Detection-with-CNNs-for-Industrial-Surface-Inspection Public

   Paper replication for B. Staar et al “Anomaly detection with convolutional neural networks for industrial surface inspection,” Procedia CIRP, vol. 79, pp. 484–489, 2019.

   Jupyter Notebook 4 2

3. AROM-DRL_Adaptive-Routing-Optimization-for-QoS-aware-SDNs-using-Deep-Reinforcement-Learning AROM-DRL_Adaptive-Routing-Optimization-for-QoS-aware-SDNs-using-Deep-Reinforcement-Learning Public

   The purpose of this project is to introduce an Adaptive RO Model for QoS-aware SDNs using DRL that dynamically considers various QoS parameters to generate a dynamic action-reward strategy.

   Python 52 13

4. Skin-Lesion-Classification-using-CNN Skin-Lesion-Classification-using-CNN Public

   The purpose of this project is to correctly classify the skin lesion category present in an image, by building the most accurate ML model. 4 different CNN architectures were used and evaluated.

   Jupyter Notebook 1 5

5. Building-A-Statistical-Based-And-LSTM-Based-Anomaly-Detection-Algorithm Building-A-Statistical-Based-And-LSTM-Based-Anomaly-Detection-Algorithm Public

   The purpose of this program is to detect anomalies in real-life time series data by building (and evaluating) a gaussian-based Anomaly Detection (AD) algorithm and an LSTM-based AD algorithm.

   Jupyter Notebook 1

6. PlantsvsZombies PlantsvsZombies Public

   Done with C++ on Qt-Creator

   C++