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Based on our record, AWS Glue should be more popular than machine-learning in Python. It has been mentiond 13 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.
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy to prepare and load data for analysis. It helps bridge the gap between our MongoDB Atlas data and the services we'll use for recommendation. - Source: dev.to / about 2 months ago
AWS Glue is a fully managed extract, transform, and load (ETL) service provided by Amazon Web Services (AWS). It is designed to make it easy for users to prepare and load their data for analysis. AWS Glue simplifies the process of building and managing ETL workflows by providing a serverless environment for running ETL jobs. - Source: dev.to / 3 months ago
It is serverless data integration service to allow you to easily scale your workloads in preparing data and moving transformed data into a target location. - Source: dev.to / 10 months ago
So in the next post, we'll do that: We'll take what we've done here, add a few more components with Pulumi and AWS Glue, and wire it all up with a few magical lines of Python scripting. - Source: dev.to / over 1 year ago
Once it's in a Data Lake then you have different options depending on the analytics you need. For more advanced constant analytics then you could look into Amazon Kinesis Data Analytics instead of Firehose to S3, but for Ad-Hoc queries then this is where Glue and Athena come in. - Source: dev.to / over 1 year ago
After that you should probably look at some very basic ML tutorials. I just googled it, I have no idea if this is good https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: about 1 year ago
Few different approaches based on search engine 'ml with python': Work though use cases / examples : https://www.databricks.com/resources/ebook/big-book-of-machine-learning-use-cases On-line class(es) / step by step projects: * https://bootcamp-sl.discover.online.purdue.edu/ai-machine-learning-certification-course * https://www.w3schools.com/python/python_ml_getting_started.asp *... - Source: Hacker News / over 1 year ago
MLE: ALL OF THE ABOVE (this is important - pure machine learning skills generally won’t make you hireable unless you’re doing a PhD and/or are a genius) Plus: 1. https://machinelearningmastery.com/machine-learning-in-python-step-by-step/ 2. https://www.coursera.org/learn/machine-learning 3. https://www.3blue1brown.com/topics/neural-networks. Source: about 2 years ago
Have you seen this? https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 2 years ago
Machine learning models Fine-tune existing machine learning models for improved accuracy, or create your own custom models. - Source: dev.to / over 2 years ago
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Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
AWS Database Migration Service - AWS Database Migration Service allows you to migrate to AWS quickly and securely. Learn more about the benefits and the key use cases.
BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
Skyvia - Free cloud data platform for data integration, backup & management
Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.