Based on our record, Google Cloud Functions should be more popular than Amazon Comprehend. It has been mentiond 43 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 first reason is that serverless architectures are inherently scalable and elastic. They automatically scale up or down based on the incoming workload without requiring manual intervention through serverless compute services like AWS Lambda, Azure Functions, or Google Cloud Functions. - Source: dev.to / 13 days ago
The FaaS platform gained a lot of popularity which resulted in many competitors. There was OSS providers like OpenFaaS or Fission. There were of course the commercial versions to like Azure Functions and Google Cloud Functions. - Source: dev.to / 21 days ago
One of the issues developers can encounter when developing in Cloud Functions is the time taken to deploy changes. You can help reduce this time by dynamically loading some of your Python classes. This allows you to make iterative changes to just the area of your application that you’re working on. - Source: dev.to / 6 months ago
I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights. Source: 8 months ago
Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment. - Source: dev.to / 10 months ago
Would you like additional capabilities like connecting to Machine Learning, Dashboards and Quicksight and leveraging other tools like Comprehend. - Source: dev.to / 11 months ago
Once again, I asked ChatGPT to perform this analysis. I could have used some of the AI tools provided by AWS, like the detectSentiment API from Amazon Comprehend, but tools like ChatGPT make it so easy to just add a simple "also, tell me in one word what the sentiment is" clause to a query I'm asking. - Source: dev.to / about 1 year ago
And now we can run amplify push to create the resources in AWS. The AWS service that will be used for this functionality is Amazon Comprehend. The pricing for this service can be found here. - Source: dev.to / about 1 year ago
Amazon has developed its own NLP service called Amazon Comprehend, which is designed to extract insights and relationships from unstructured text data. Source: about 1 year ago
First, can you use a different AWS service, such as Comprehend or SageMaker? You only "pay for what you use" instead of paying for an idle server. This is especially helpful for a start up, since you don't pay a lot if you don't have a lot of customers.. Source: over 1 year ago
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.
spaCy - spaCy is a library for advanced natural language processing in Python and Cython.
Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.
FuzzyWuzzy - FuzzyWuzzy is a Fuzzy String Matching in Python that uses Levenshtein Distance to calculate the differences between sequences.
AWS Lambda - Automatic, event-driven compute service
Google Cloud Natural Language API - Natural language API using Google machine learning