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Though you may encounter the terms “datascience” 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.
While datascience and machine learning are related, they are very different fields. In a nutshell, datascience brings structure to big data while machine learning focuses on learning from the data itself. What is datascience? This post will dive deeper into the nuances of each field.
Note: throughout this blog, when I use the term “artificial intelligence,” I mean that to include other advanced analytics such as deep learning, machine learning (supervised, unsupervised, reinforcement), datamining, predictive analytics, and statistics (see Figure 1). Figure 1: The Evolution of AI, ML and DL (Source: Nvidia ).
Note: throughout this blog, when I use the term “artificial intelligence,” I mean that to include other advanced analytics such as deep learning, machine learning (supervised, unsupervised, reinforcement), datamining, predictive analytics, and statistics (see Figure 1). Figure 1: The Evolution of AI, ML and DL (Source: Nvidia ).
DRM is used by publishers, manufacturers and IP owners for digital content and device monitoring” (Techopedia 2021). The expanded business areas and roles include data governance, datascience, data policies and processes, information and records management, and compliance and privacy. “A Data Analytics.
Yes, the ancient pyramids relied not only on labor and raw materials, but on data collection and analysis. . Data collection is what we do. Today, we think of Big Data as a modern concept. Cloud storage, text mining and social network analytics are vital 21 st century tools. How United by Data connects us.
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