Google App Engine
Salesforce Platform
Dokku
Heroku
AWS Lambda
AWS Elastic Beanstalk
Google Cloud Functions
Azure Web Apps
OpenCV
Scikit-learn
Pandas
NumPy
Dataiku
Exploratory
htm.java
WEKA
Google App Engine OpenCVBased on our record, OpenCV should be more popular than Google App Engine. It has been mentiond 51 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.
In 2008, Google launched AppEngine. This product predates the formal existence of Google Cloud and can be considered Google Cloud's first offering. - Source: dev.to / 9 days ago
To deploy the app, we can use Google Cloud App Engine, which is specifically built for server-side rendered websites. After we create a new project in the Google Cloud Console, we have to configure the cql-trace-viewer application. - Source: dev.to / 12 months ago
I've read that article, but I'm thinking there are other better (and most importantly cheaper) ways of doing that, such as using App Engine (given that you have to mitigate the maximum request timeout and to make sure there are constantly exactly 1 instance running). Source: about 1 year ago
Shout out to GCP App Engine for deploying anode/Express severe. Source: about 1 year ago
If your project is a bit more complicated using next.js or react.js or angular.js, you may find some free Platfrom-as-a-Service%20is%20a%20complete%20cloud%20environment,middleware%2C%20tools%2C%20and%20more.). I have seen some of my peers using free PaaS like Heroku, Vercel and I have no experience in using PaaS but I will recommend you to use PaaS from either of the three 1. Google Cloud's Google App Engine 2.... Source: about 1 year ago
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / 1 day ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 6 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 10 months ago
I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest... Source: 10 months ago
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.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Dokku - Docker powered mini-Heroku in around 100 lines of Bash
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Heroku - Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.
NumPy - NumPy is the fundamental package for scientific computing with Python