Top 5 reasons to master no-code machine learning
By Market Trends, contributing writers for Analyticinsight.net
No-code ML is a subset that tries to make ML more accessible. To deploy AI and machine learning models, no-code ML involves adopting a no-code development platform with a visual, code-free, and frequently drag-and-drop interface. No-code ML analysts have the power of data predictions to help them move faster, which means they can help their businesses to think creatively and proactively without blowing the budget. In this video, we take you through the list of reasons to master no-code machine learning.
How big data and AI are changing the financial industry
By David Cotriss, contributing writer for NASDAQ.com
The financial industry has never been short of data, but until recently, the bulk of it has been too complex to do anything meaningful with. A little something called AI is gradually changing that. But what impact will that have on the financial industry, and which companies should we be watching?
Unlocking the power of AI with Decision Intelligence
By Atul Sharma, contributing writer for Cio.economictimes.indiatimes.com
Since the start of the pandemic, digital adoption has accelerated and is set to continue growing. Artificial Intelligence (AI) as a technology is increasingly being referenced in the context of digital transformation. Today, businesses understand the need to collect, categorize, and analyze the data generated by their users for competitive edge. Keeping this in mind, more and more CTOs are adopting an AI strategy to drive efficient and optimal outcomes of business objectives. More frequently referenced than the occasional investor update, AI strategy is being queried at the company board level, and there is immense pressure on CTOs to deliver on this opportunity.
Machine learning by intuition
By Bradley van Paridon, contributing writer for Advancedsciencenews.com
Human–computer interfaces, a long sought-after goal, would open new worlds. Disabled people could regain autonomy, people could access information and operate seamlessly in a digital world. This goal is yet to be realized because training machines to follow our mental commands, such as move a cursor across the screen, is a complicated and tedious process. Now, by approaching the problem of this machine learning from a brand-new angle, researchers from the University of Helsinki are drastically improving how we can interface with machines. Rather than teaching the computer to do something when we ask it, the machine is now capable of learning what we want it to do without being told.
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