Название: The Future of Analytics: The New Landscape of Artificial Intelligence and Machine Learning Applications
Автор: Dan Darnell, Rafael Coss, Patrick Hall
Издательство: O’Reilly Media, Inc.
Год: 2020
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

As enterprise adoption of AI and machine learning software becomes more commonplace, what does your company need to know to invest wisely in these technologies? In this detailed report, authors Rafael Coss, Dan Darnell, and Patrick Hall provide valuable information to help managers and practitioners make sound decisions for your organization in this commercial landscape. Analytics adoption has driven a wave of digital transformation across industries, but many projects face significant drawbacks. Through the course of this report, you'll examine two of these issues: how the lack of involvement and access by domain experts and end users causes projects to lose focus and why predictive models often end up as services rather than part of new or existing applications.

Artificial intelligence (AI) is the ability for machines to perform tasks that people generally do, such as making inferences and decisions based on data, identifying trends, sorting images, responding to speech or text, and more. Traditionally, AI in the form of machine learning is used to create models that predict what will happen in the future based on past information. These models are used in batch processes to score or categorize records offline, or in real time to provide predictions in decision-making processes.

"Data scientist" has become the hottest title and the hardest to fill position for many organizations. While many data analysts changed their titles to capture the new wave of interest, they lack the skills in languages like Python and R and an understanding of modeling algorithms and techniques needed for predictive model development. The lack of qualified data scientists in the market has put many companies on the slow track in AI development. Even with qualified data scientists on staff, companies find their output is limited due to the handcrafted nature of their work and the high maintenance costs of such models in production.