2020-05-11 · This class will start with a brief overview of neural networks, then spend the majority of the class demonstrating how to apply neural networks to ...

natural-language-processing course carnegie-mellon neural-networks

A Tensorflow-based framework to ease the training of generative models

computer-vision generative-adversarial-networks tensorflow deep-learning

2020-04-01 · Combine interpretability of a decision tree with accuracy of a neural network.

decision-trees neural-networks deep-learning research

2020-04-04 · We all know about meta-learning and pseudo labeling but what if we combine the two techniques for semi-supervised learning? Can it be any beneficial?

semi-supervised-learning meta-learning machine-learning deep-learning

2020-03-09 · Optimization technique that operates directly on gradients by centralizing their vectors to zero mean.

normalization optimization gradients neural-networks

This repository provides tutorial code in C++ to learn PyTorch by building CNNs, RNNs, etc. Tutorials are divided into three sections based on complexity.

pytorch c++ torch torchscript

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

autograd neural-networks toolkit

In this post, we'll explain how to initialize neural network parameters effectively.

interactive visualization weights initialization

Visualizing parameter optimization

optimization training parameter-optimization convolutional-neural-networks

Tinker With a Neural Network Right Here in Your Browser.

interactive visualization playground tensorflow

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