kubeflow
fashion-mnist
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kubeflow | fashion-mnist | |
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3 | 15 | |
13,552 | 11,439 | |
1.3% | 1.8% | |
8.5 | 0.0 | |
6 days ago | almost 2 years ago | |
TypeScript | Python | |
Apache License 2.0 | MIT License |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
kubeflow
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Machine Learning Orchestration on Kubernetes using Kubeflow
If you are looking for bringing agility, improved management with enterprise-grade features such as RBAC, multi-tenancy and isolation, security, auditability, collaboration for the machine learning operations in your organization, Kubeflow is an excellent option. It is stable, mature and curated with best-in-class tools and framework which can be deployed in any Kubernetes distribution. See Kubeflow roadmap here to look into what's coming in the next version.
fashion-mnist
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Logistic Regression for Image Classification Using OpenCV
In this case there's no advantage to using logistic regression on an image other than the novelty. Logistic regression is excellent for feature explainability, but you can't explain anything from an image.
Traditional classification algorithms but not deep learning such as SVMs and Random Forest perform a lot better on MNIST, up to 97% accuracy compared to the 88% from logistic regression in this post. Check the Original MNIST benchmarks here: http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/#
- How to produce data visualizations like this?
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A New Google AI Research Study Discovers Anomalous Data Using Self Supervised Learning
New Google AI research introduces a 2-stage framework that uses recent progress on self-supervised representation learning and classic one-class algorithms. This framework is simple to train and shows SOTA performance on various benchmarks, including CIFAR, f-MNIST, Cat vs. Dog, and CelebA. Following that, they offer a novel representation learning approach for a practical industrial defect detection problem using the same architecture. On the MVTec benchmark, the framework achieves a new state-of-the-art.
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Machine Learning Orchestration on Kubernetes using Kubeflow
About the Dataset Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image associated with a label from 10 classes. We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the exact image size and structure of training and testing splits. source: https://github.com/zalandoresearch/fashion-mnist
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[P] Why are stacked autoencoders still a thing?
fashion-mnist
What are some alternatives?
kserve - Standardized Serverless ML Inference Platform on Kubernetes
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
BentoML - Build Production-Grade AI Applications
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
kmnist - Repository for Kuzushiji-MNIST, Kuzushiji-49, and Kuzushiji-Kanji
zozo-shift15m - SHIFT15M: Fashion-specific dataset for set-to-set matching with several distribution shifts
pipelines - Machine Learning Pipelines for Kubeflow
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
tape - Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
Anime-face-generation-DCGAN-webapp - A port of my Anime face generation using Pytorch into a Webapp
fashion-mnist-kfp-lab - A notebook showing how to easily convert a current notebook you have to a notebook that can be run on Kubeflow Pipelines.