UPDATE: Downloading data objects hosted in Collaboratory is no longer For convenience, when files to be downloaded are all from a single repository, it is
Google Colaboratory Notebooks and Repositories. Contribute to firmai/awesome-google-colab development by creating an account on GitHub. Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style" (http://arxiv.org/abs/1508.06576) in Keras 2.0+ - titu1994/Neural-Style-Transfer Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts - minimaxir/gpt-2-simple Mitigate machine learning bias to ensure data ethics in U.S. national home mortgage dataset. - YuexiSC/debias-in-machine-learning Provide an input CSV and a target field to predict, generate a model + code to run it. - minimaxir/automl-gs Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code. - minimaxir/textgenrnn Contribute to markriedl/easygen development by creating an account on GitHub.
Comparing free services for running an interactive Jupyter Notebook in the cloud: Binder, Kaggle Kernels, Google Colab, Azure Notebooks, CoCalc, Datalore. If you wish to download data for specific tutorials, use the list below to find the correct dataset to download and use. Note that Colab has its own data download mechanism (see Colab install instructions). In this Blog, we will learn about Jupyter Notebook and Google Colab. We will also learn basic features of notebook and writing code on notebooks. You can greatly enhance face details of src faceset by using Topaz Gigapixel software. example before/after https://i.imgur.com/Gwee99L.jpg Download it from torrent https://rutracker.org/forum/viewtopic.php?t=5757118 Example of workflow: A list of deep learning implementations in biology - hussius/deeplearning-biology
Issue #4665 would help us in our work to integrate Dataverse with Binderhub. Our goal with the integration is to allow anyone browsing datasets in Dataverse to instantly launch a Binderhub-based reproducible compute environment. CryptoCurrency prediction using Deep Recurrent Neural Networks - manthanthakker/BitcoinPrediction ️Machine learning-based parameterizations in climate models: a case-study on convection - edenau/Machine-Learning-Climate-Parameterization :zap: Python package for Radex grid calculation. Contribute to astropenguin/ndradex development by creating an account on GitHub. 3D printing projects by Derek Quenneville / techknight
Feb 15, 2019 Mounting the Google Drive to Google Colab; Downloading the dataset For dataset with multiple zip files like the example, I tend to change
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts - minimaxir/gpt-2-simple Mitigate machine learning bias to ensure data ethics in U.S. national home mortgage dataset. - YuexiSC/debias-in-machine-learning Provide an input CSV and a target field to predict, generate a model + code to run it. - minimaxir/automl-gs Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code. - minimaxir/textgenrnn Contribute to markriedl/easygen development by creating an account on GitHub. Portrait segmentation with mobile-unet using keras - anilsathyan7/Portrait-Segmentation A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.
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