Amazon S3 (Amazon Simple Storage Service) is the storage platform by Amazon Web Services (AWS) that provides an object storage with high availability, low latency and high durability. S3 can store any type of object and can serve as storage for internet applications, backups, disaster recovery, data archives, big data sets and multimedia.
Based on our record, Amazon S3 should be more popular than Keras. It has been mentiond 175 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 27 days ago
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / 2 months ago
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / 3 months ago
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / about 1 year ago
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago
When dealing with image processing, we can use S3 and our own transformers, but in order to simplify development, better to use some free SaaS solution. We can rely on it when dealing with a common set of problems. Every image uploaded can be dynamically transformed to any thumbnail size, file format, and quality so we are able to test different settings that best fit user expectations. All images can be... - Source: dev.to / about 1 month ago
The meta-data and model artifacts from experiment tracking can contain large amounts of data, such as the training model files, data files, metrics and logs, visualizations, configuration files, checkpoints, etc. In cases where the experiment tool doesn't support data storage, an alternative option is to track the training and validation data versions per experiment. They use remote data storage systems such as S3... - Source: dev.to / about 1 month ago
In this tutorial, I will walk you through building a quick static site by doing a static build using ReactJS & create-react-app, then show you how to deploy that static site on AWS using S3 buckets as well as how to cache it & add SSL certificates with CloudFront CDN & Certificate Manager. - Source: dev.to / about 1 month ago
The main stars for deploying WASM on S3 are CloudFront and of course S3. Those two services will do the heavy lifting with our compiled WASM distribution. - Source: dev.to / about 2 months ago
Event Producers: Generate streams of events, which can be implemented using straightforward microservices with AWS Lambda (for serverless computing), Amazon DynamoDB Streams (to captures changes to DynamoDB tables in real-time), Amazon S3 Event Notifications (Notify when certain events occur in S3 buckets) or AWS Fargate (a serverless compute engine for containers). - Source: dev.to / 2 months ago
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
AWS Lambda - Automatic, event-driven compute service
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Google Cloud Storage - Google Cloud Storage offers developers and IT organizations durable and highly available object storage.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Minio - Minio is an open-source minimal cloud storage server.