A set of notebooks that leverage classical ML algorithms and DL neural nets using TF, Keras and Theano to address a series of issues in the field of conservation and biology.
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Updated
Jul 29, 2020 - Jupyter Notebook
Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.
A set of notebooks that leverage classical ML algorithms and DL neural nets using TF, Keras and Theano to address a series of issues in the field of conservation and biology.
📓 Tutorials for the pidgan package
Logistic regression, deep learning, YOLO, Recursive Neural Networks, GAN and Conditional GAN
Just some notebooks I wrote to research some fun stuff in hobby time
Backup for kaggle.com notebooks
Collection of notebooks created while learning about NerualNets
Toy notebooks as research preparation into generative adversarial networks
MVI course at FIT CTU
Notes and Jupyter notebooks exploring deep learning and Tensorflow framework
Face generation with deep convolutional generative adversarial network using PyTorch and Jupyter Notebook.
This library contains executable notebooks (colab) with a Generative Art of Deep Neural Networks
A simple well-documented tutorial on implementing a 1D GAN on Keras using a Python Jupyter Notebook
Important Resources and Workspace Notebooks as mentioned in the Udacity Deep Learning Nanodegree. WELCOME to Udacity DLND Workspace
📓 Scripts and logics to train tracking models for the flash simulation of the LHCb experiment
This repository leverages Generative Adversarial Networks (GANs) to enhance image resolution for various applications, using the Super-Resolution GAN (SRGAN) architecture. The project includes a Jupyter Notebook for model training and a detailed research paper documenting the methodology and results.
This Repository contain an IPython notebook of an example implementation of conditional Deep Convolutional Generative Adversarial Networks or cDCGAN or DC cGAN using Tensorflow.Keras Funtional API.
Tensorflow (mainly Keras) implements different GANs with Jupyter Notebook
Generating Bangla handwritten digits using GAN
Released June 10, 2014