IBM Big Data Hub
SEPTEMBER 19, 2023
Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.
IBM Big Data Hub
JULY 6, 2023
While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.
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IBM Big Data Hub
AUGUST 11, 2023
Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.
IBM Big Data Hub
AUGUST 28, 2023
One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? When used strategically, text-mining tools can transform raw data into real business intelligence , giving companies a competitive edge. How does text mining work?
IBM Big Data Hub
AUGUST 15, 2022
Across various industries, regulatory requirements for model fairness and trustworthy AI aim to prevent biased models from entering production cycles. How does a data architecture impact your ability to build, scale and govern AI models? Data risk assessment. Detecting and defining bias and unfairness isn’t easy.
Info Source
OCTOBER 6, 2020
The Alteryx APA Platform unifies analytics, data science and data-centric process automation in one self-service platform. ABBYY brings process intelligence to both data and operational processes to automate otherwise complex hand-offs. “For
IBM Big Data Hub
NOVEMBER 30, 2022
So, it’s crucial for companies that want to add specific AI capabilities to their applications or workflows to do so without expanding their technology stack, hiring more data science talent, or investing in expensive supercomputing resources. IBM partners are making use of embeddable AI in various ways and across different industries.
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