Composable Analytics
Jupyter
IBM ILOG CPLEX Optimization Studio
Amadea
PurpleCube
RapidMiner Studio
Pyramid Analytics
Tibco Data Science
NumPy
Pandas
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
Composable AnalyticsBased on our record, NumPy seems to be a lot more popular than Composable Analytics. While we know about 108 links to NumPy, we've tracked only 1 mention of Composable Analytics. 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.
- Front-End UI Developers passionate about creating well-architected user interfaces and fluent in current best practices for responsive and accessible design. - Junior and Senior level Software Engineers that have the ability to work across all layers of the application, from back-end databases to the UI. - Data engineers and data scientists knowledgeable in developing and training data models and building... - Source: Hacker News / almost 3 years ago
Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 9 months ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 3 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 / 6 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
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
IBM ILOG CPLEX Optimization Studio - IBM ILOG CPLEX Optimization Studio is an easy-to-use, affordable data analytics solution for businesses of all sizes who want to optimize their operations.
OpenCV - OpenCV is the world's biggest computer vision library
Amadea - Amadea is the leading integrated Data Science platform, empowering data analysts and data scientists to discover the insights that drive business success.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
