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2d-convolution

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TF-1D-2D-ResNetV1-2-SEResNet-ResNeXt-SEResNeXt

Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).

  • Updated Jan 27, 2022
  • Jupyter Notebook
Noise2Noise-Lite-two-ligther-versions-of-the-famous-AI-denoiser-for-small-images

Noise2Noise is an AI denoiser trained with noisy images only. We implemented a ligther version which trains faster on smaller pictures without losing performance and an even simpler one where every low-level component was implemented from scratch, including a reimplementation of autograd.

  • Updated Sep 25, 2022
  • Jupyter Notebook

A collection of Jupyter notebooks containing various MNIST digit and fashion item classification implementations using fully-connected and convolutional neural networks (CNNs) built with TensorFlow and Keras. 2020.

  • Updated Nov 12, 2020
  • Jupyter Notebook

NLP Project - Sentence Classification - Toxicity- Approx 20,000 comments - ranging from 2 to 30 words. Balanced Data Set. 1. Traditional, pre-2010 NLP and ML techniques used. 2. Dense Word Vectors - w2v & Glove, sentence vector created from averaged word vectors, ANN. 3. Glove combined with bi-LSTMs and 2D Convs.

  • Updated Dec 25, 2021
  • Jupyter Notebook

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