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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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