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.
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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 / 8 days 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 / 9 days 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 / 19 days 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 1 month 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 / about 1 month ago
Have you consider dataquest.io ? I m thinking on subscribing there, the learning path since well balanced between theorical and practical knowledge, plus there are some pet projects initiaves. Source: about 1 year ago
I did a lot of planning, reporting and optimizations based on data when I was in digital media, so I've been applying to data focused roles. In my free time, I've also been learning Data Science via dataquest.io, hoping to take my analysis to the next level, learn new skill sets, and keep coding. Source: over 1 year ago
I recommend dataquest.io. It's an intuitive way to learn the fundamentals if you'd rather not study in a more formal manner. Source: over 1 year ago
Does it need to be a postgrad degree? If you want more hands on you might be better using Dataquest. Source: about 2 years ago
I am using Dataquest to learn Python for Data Science there. I also got a book from O'Riley called Data Science Handbook and the Automating the Boring Stuff with Python book. SQL is good to know and comes in handy. Source: about 2 years ago
AWS Lambda - Automatic, event-driven compute service
Gyana - Intuitive easy-to-use report and dashboard tool to stop wasting time on repetitive and tedious tasks.
Google Cloud Storage - Google Cloud Storage offers developers and IT organizations durable and highly available object storage.
Deepnote - A collaboration platform for data scientists
Minio - Minio is an open-source minimal cloud storage server.
Amie - GitHub for research and data science