Based on our record, NumPy should be more popular than Google App Engine. It has been mentiond 107 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 NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months 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 / 11 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: 11 months ago
Shout out to GCP App Engine for deploying anode/Express severe. Source: 12 months 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
UNIX is irrelevant on the cloud, unless one is stuck deploying legacy workloads on VMs, this is what we use in modern applications not stuck in the past. https://aws.amazon.com/eks/ https://azure.microsoft.com/en-us/products/kubernetes-service https://cloud.google.com/kubernetes-engine/ https://cloud.google.com/appengine https://azure.microsoft.com/en-us/products/app-service https://aws.amazon.com/lambda/... - Source: Hacker News / about 1 year ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
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.
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.
OpenCV - OpenCV is the world's biggest computer vision library
Dokku - Docker powered mini-Heroku in around 100 lines of Bash