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Gradient Python SDK end-to-end example

Train and deploy a model with the Gradient SDK using the classic MNIST handwritten digits dataset and TensorFlow

  • Image Processing

Generate Images with a Variational Autoencoder (VAE)

Using Keras and the fashion-MNIST dataset to generate images with a VAE

  • Autoencoder

Classifying Clothing with Fashion MNIST

Train a neural network model to classify images of clothing using the Fashion MNIST dataset

  • Classification

Welcome to Gradient Notebooks 👏

A quick how-to guide on using Gradient Notebooks

  • Gradient

Practical Deep Learning for Coders by fast.ai (v3 2019)

Run the previous version (v3) of Practical Deep Learning for Coders by fast.ai

  • Fast.ai

Logistic Regression with Scikit-Learn

Train a logistic regression model based on the MNIST dataset.

  • Scikit-Learn

Sentiment Analysis in Pytorch

Sentiment Analysis using several different methods in PyTorch

  • PyTorch

Text Generation with GPT-2

Generate text using the state-of-the-art model from Open.ai

  • Language

Image Segmentation with TensorFlow

Using TensorFlow to determine objects and surroundings in images

  • Classification

Simple Edge Detection with OpenCV

Finding edges of the images using Canny edge detector

  • OpenCV

Bacteria Classification with fast.ai

Using fast.ai to build a state of the art bacterial classifier with the DIBaS dataset

  • Fast.ai

PyTorch Tutorial: Working with Tensors

Learn the essentials of working with tensors in PyTorch

  • PyTorch
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