In many data analytics use cases ... Take Streamlit as an example. As a Python-based library, it’s specifically designed for developers and ML engineers to rapidly build and share ML and ...

It combines Python’s data analysis and visualization libraries with Excel’s features ... Python in Excel is revolutionizing the way data analytics is conducted. It offers a unique blend ...

Python continues to be a ... For example, if you’re working on data analysis, instead of writing code to sort or filter data, you can use a library that already has these capabilities.

Intel is helping this trend along with its acceleration library, called DAAL (Data Analytics Acceleration ... with language bindings for C++, Java, and Python. DAAL handles BIG data much better ...

The core of R was developed during the 1970s and since then, many libraries (such as the Tidyverse for data manipulation) have been developed to greatly extend the functionality of the language.

Dask, a Python library for parallel computing ... API or converting to cuDF dataframes. Visualizing data is fundamental, both within the analytics workflow and for presenting or reporting results.

RAPIDS is a suite of open-source software libraries for executing end-to-end data science and analytics pipelines ... whose goal is to natively scale Python. As Python is the language of choice ...

building dashboards with IBM Cognos Analytics, and visualizing data using Python libraries. Individuals with the certificate can describe data ecosystems and compose queries to access data in ...