This rubric covers the use of statistical tools working on large datasets to create models and derive inferences, as well as coverage of the field in its entirety. This differs from machine learning primarily in that the latter focuses on functional gradient analysis or neural networks (kernels) to derive models.
Effective data management is critical to any organization’s success in today’s data-driven world. With the exponential growth of data, businesses need to implement robust strategies… Read More »Mastering data management: Efficient strategies for success
From ensuring that mobile apps function smoothly to facilitating personalized recommendations and targeted ads, data engineering powers the digital experiences that have become part of… Read More »Data engineering career guide
Two roads diverged in a wood, and I;I took the one less traveled by,And that has made all the difference. — Robert Frost At certain… Read More »FAIR knowledge: The key precondition for trusted generative AI
Written by Venkata Nori and Kshitij Gopali. Introduction As technology is evolving, most companies in the world are adopting advanced mechanisms for their daily tasks… Read More »Seamless integration of data from unconventional source systems into Business Intelligence using data science techniques
A recent interview by Medical Device Network with GlobalData medical analyst Alexandra Murdoch shares interesting insights into cybersecurity for medical devices.
In the contemporary digital landscape, data has emerged as a critical asset for organizations aiming to make informed decisions and foster innovation. Data analytics can… Read More »Understanding the difference: Data analyst, data scientist, and data engineer
This cutting-edge area of AI focuses on building models that can create original material, including music, images, text, and even entire virtual worlds.
In the ever-evolving landscape of the digital era, the relentless quest for deriving actionable insights from a sea of information has become the cornerstone of… Read More »Cracking the code: The rising demand for data scientists in various industries
E-commerce has improved technology and convenience for consumers globally. Fraud is a problem in e-commerce. Merchants and platforms fight fraud to protect their businesses and… Read More »In fraud detection for e-commerce: How does anomaly detection fit in and what are the key approaches?
Working as a data scientist is the dream of many IT professionals these days. It is no secret that data science is a skyrocketing field… Read More »Are data science certifications the gateway to competitive pay?
