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Applications of Machine Learning in the Cryptosphere
This article discusses the benefits and drawbacks of applying Machine Learning in the Crypto-Sphere. While Machine Learning has benefits such as Flow Analysis and Address Classification, it also has drawbacks such as error occurrences. Read the whole thing to find out what the final verdict is!
The Pros and Cons of Machine Learning Applications in the Crypto-Sphere!
Let’s get started!
Deloitte Global predicts that the number of machine learning applications and implementations being used in the business industry will double by 2020! Another forecast by IDC says that spending on AI and Machine Learning will grow from $12B in 2017 to $57.6B by 2021.
Amazing it is! Isn’t it? With such a huge buzz around, it’s quite difficult to ignore a technology that is as impactful as Machine Learning (ML). It is an advanced application of AI that allows systems to perform tasks without being explicitly programmed. Machine Learning has NOW become a centerpiece of all strategies being used in the market space. This is why Greg Papadopoulo said this: “Machine Learning is going to result in a real revolution.”
It is “the craft of having computers make decisions without providing explicit instructions, thereby allowing the computers to pattern match complex situations and predict what will happen”, said Venkat Venkataramani, the co-founder and CEO of Rockset,
It is Machine Learning that people often talk about when they use the umbrella term “AI.” One can see a number of industries involved in leveraging ML benefits these days. Cryptosphere is one of these. So it’s worth taking the time to look at some of the incredible ML capabilities being deployed in the Crypto space. Here you go.
