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

    MATLAB 2 4

  2. 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 12 6

  3. 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 6 4

  4. 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. 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. Forked from feature-engine/feature_engine

    Feature engineering package with sklearn like functionality

    Python

60 contributions in the last year

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Contribution activity

August 2022

ttungl has no activity yet for this period.

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