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1. Reinforcement-Learning Reinforcement-Learning Public

   Reinforcement Learning in OpenAI Gym and custom simulator environments.

   Python 1

2. PaDiM-Patch-Distribution-Modeling PaDiM-Patch-Distribution-Modeling Public

   Jupyter Notebook

3. Stanford-Cars-Dataset-Vehicle-Recognition Stanford-Cars-Dataset-Vehicle-Recognition Public

   Transfer Learning using state-of-the-art CNN architectures (ResNet34 and Xception). Class engineering, learning rate/weight decay tuning and one-cycle policy are implemented.

   Jupyter Notebook 9 2

4. GTSRB-Traffic-Sign-Recognition-Part1 GTSRB-Traffic-Sign-Recognition-Part1 Public

   Traffic Sign Recognition Project Part I (RandomForest, XGBoost, NNs, etc) utilizing the RandomSearch hypertuning algorithm. Thresholding, edge detection, PCA and feature selection are explored.

   Jupyter Notebook 1

5. GTSRB-Traffic-Sign-Recognition-Part2 GTSRB-Traffic-Sign-Recognition-Part2 Public

   Traffic Sign Recognition Project Part II focusing on RandomForest and SVM. HOG features are introduced. Combinations of feature extraction and feature selection/PCA are analyzed.

   Jupyter Notebook 2 1

6. GTSRB-Traffic-Sign-Recognition-Part3 GTSRB-Traffic-Sign-Recognition-Part3 Public

   Traffic Sign Recognition Project Part III focusing on ConvNets, using keras and tensorflow. Learning rate hypertuning is explored.

   Jupyter Notebook