Cyclr
Zapier
ifttt
Boomi
Make.com
Cloud Elements
Microsoft Power Automate
Datadog
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Cyclr is a SaaS integration toolkit for SaaS platforms and app developers, providing a complete solution to serve your customers integration needs -- all from within your application. Cyclr enables you to deliver integrations to 100s of popular apps and services with low-code and low engineering overhead. Cyclr also handle all the updates, cutting development teams integration maintenance overhead.
Integrations are created using a drag and drop designer, enabling members of your wider teams (customer success, sales and support) to build and publish new integrations and workflows in minutes.
Integrations can then be published directly into your application so your users can self-serve. This can be achieved by building your own UI on top of Cyclr's fully featured API, or through deploying their white-labelled and completely customisable embedded marketplace.
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This is the best platform to use. You can rely on this platform for different kind of work. Highly recommended
Based on our record, NumPy seems to be a lot more popular than Cyclr. While we know about 107 links to NumPy, we've tracked only 1 mention of Cyclr. 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.
Other good solutions with similar features would be PieSync, Automate.io, Zapier, Cyclr, Workato. All of these app integrations allow you to connect your Mailchimp account with your SaaS app (in your case with your database). Source: about 3 years ago
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
Zapier - Connect the apps you use everyday to automate your work and be more productive. 1000+ apps and easy integrations - get started in minutes.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Boomi - The #1 Integration Cloud - Build Integrations anytime, anywhere with no coding required using Dell Boomi's industry leading iPaaS platform.
OpenCV - OpenCV is the world's biggest computer vision library