Pinned

1. Machine-Learning

   Machine learning techniques, such as Linear Regression, Logistic Regression, Neural Networks (feedforward propagation, backpropagation algorithms), Diagnosing Bias/Variance, Evaluating a Hypothesis…

   MATLAB 1 2

2. Deep-Learning

   Implemented the deep learning techniques using Google Tensorflow that cover deep neural networks with a fully connected network using SGD and ReLUs; Regularization with a multi-layer neural network…

   Jupyter Notebook 8 5

3. HeteroArchGen4M2S

   HeteroArchGen4M2S: An automatic software for configuring and running heterogeneous CPU-GPU architectures on Multi2Sim simulator. This tool is built on top of M2S simulator, it allows us to configur…

   GLSL 3 2

4. SDC-term1-Traffic-Sign-Classifier

   Built and trained a deep neural network to classify traffic signs, using TensorFlow. Experimented with different network architectures. Performed image pre-processing and validation to guard agains…

   HTML 1 1

5. SDC-term1-Behavioral-Cloning

   Built and trained a convolutional neural network to drive the car itself autonomously in a simulator using Tensorflow (backend) and Keras. Experimented with a modified Nvidia architecture. Performe…

   Python 5 2

6. SDC-term1-Advanced-Lane-Finding

   Detected highway lane boundaries on a video stream with OpenCV image analysis techniques, including camera calibration matrix, distortion correction, color transforms, gradients, etc., to create a …

   HTML 1 1