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Test-Time Data Augmentation
Tutorial on how to properly implement test-time image data augmentation in a production environment with limited computational resources.
data-augmentation keras production tensorflow
A 2020 guide to Semantic Segmentation
Concept of image segmentation, discuss the relevant use-cases, different neural network architectures involved in achieving the results, metrics and ...
semantic-segmentation image-segmentation computer-vision segmentation
Flexible and powerful tensor operations for readable and reliable code. Supports numpy, pytorch, tensorflow, and others.
einops numpy pytorch tensorflow
How to Detect Data-Copying in Generative Models
I propose some new definitions and test statistics for conceptualizing and measuring overfitting by generative models.
generative-modeling data-copying generative-adversarial-networks variational-autoencoders
Hyperparameter Optimization for AllenNLP Using Optuna
🚀 A demonstration of hyperparameter optimization using Optuna for models implemented with AllenNLP.
hyperparameter-optimization optuna allennlp allenai
Data Science Meets Devops: MLOps with Jupyter, Git, & Kubernetes
An end-to-end example of deploying a machine learning product using Jupyter, Papermill, Tekton, GitOps and Kubeflow.
production end-to-end mlops gitops
Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX.
onnx pytorch model-serving transformers
Quick Draw Sketches Classification using PyTorch
Alternative project to overused MNIST dataset with similar objective and data set. The Quick Draw Dataset is a collection of 50 million drawings in 28x28 ...
image-classification convolutional-neural-networks feed-forward-neural-networks deep-learning
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