Things that I use while building the models
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Updated
May 12, 2019 - Python
Things that I use while building the models
An Interactive web-app that allows people to train live Neural-Network with Custom Inputs and Live feedback.
Visualising your neat algorithm networks with the manim library. Works specifically for the neat-python library
Collection of Jupyter Notebooks on neural networks using PyTorch and Stochaster involving detailed mathematics.
We will visualize the style transfer output produced by monet_generator_model. We take 5 sample images that are photos of beautiful landscapes in the original dataset and feed them to the model.
Nerou - neural webs engine with a graphical interface
A collection of Latex (tikz) code to Visualize Neural Network
An impementation of CNN Fixations for PyTorch.
NN Forge: Design neural networks visually with our intuitive GUI, then generate clean Python code to jumpstart your deep learning projects.
MNIST code with different classifier using sklearn and tflearn library in Python
Real-time Object Detection and Neural Network Training Visualization
A Neural Network Visualizer Web Application On The MNIST Dataset.
A python program to visualize simple neural networks
Part of the experiments in "A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations"
A set of APIs for 3D Visualization of Neural Networks (NN) in Python using the Panda3D game engine. The NN can be modeled using TensorFlow or a custom built model.
A web app made using Flask and Streamlit to visualise the workings of a Neural Network
NNV - Neural Network Visualizer
A generic implementation of multi layer perceptron neural networks, including some visual tools. Contains example of using the neural network classes for function approximation.
This repository consists the code for the paper titled Introspective Learning : A Two-Stage Approach for Inference in Neural Networks
Training and web visualization of digit recognition feedforward neural network using brain.js and three.js
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