Cradle
ReqView
Jama Connect
Serena Dimensions RM
Accompa
Enterprise Tester
Micro Focus Atlas
Jama
NumPy
Pandas
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
Cradle integrates your entire project lifecycle in one, massively scalable, integrated, multi-user product. Whether your projects are small and local, large and distributed, or anywhere in between, Cradle can solve all your agile, requirements management, model-driven development, defect tracking and test management needs in one place. With its unrivalled feature set, incredible flexibility, simple configuration and low cost, Cradle is the ideal choice if you are new to agile methods, requirements management or systems engineering.
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Based on our record, NumPy seems to be more popular. 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 / 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 / 3 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 / 7 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
ReqView - Simple and powerful requirements management tool enabling easy requirements gathering, traceability tracking and offline collaboration.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Jama Connect - The Leader in Requirements Management Solutions
OpenCV - OpenCV is the world's biggest computer vision library
Serena Dimensions RM - Serena Dimensions RM is a web application to improve the definition and management of requirements across the product lifecycle.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.