How Machine Learning Is Becoming The Super Power Of Computer Science?

[arpit dixit]

The most exciting branch of Artificial Intelligence, Machine Learning is all around us in this modern era. As Facebook suggesting the stories in your feed, same Machine Learning brings out the power of data in a new way. It works on the phenomenon of working on the development of computer programs that can access data and perform tasks automatically through predictions and detection, Machine Learning enables computer systems to learn and improve from experience continuously.  

What is Machine Learning

If talking about Machine Learning definition then, it is a core sub-area of Artificial Intelligence (AI). Machine Learning applications learn from experience (well data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. In other words, with Machine Learning, computers find insightful information without being told where to look. Instead, they do this by leveraging algorithms that learn from data in an iterative process. While the concept of Machine Learning has been around for a very long time (think of the WWII Enigma Machine), the ability to automate the application of complex mathematical calculations to Big Data has been gaining momentum over the past several years. At a high level, ML is the ability to adapt to new data independently and through iterations.  Basically, applications learn from previous computations and transactions and use “pattern recognition” to produce reliable and informed results.

[johnvickyy]

Good information, Actually im searching for machine learning certification training program, will u explain about the duration and certification training providers that could helpful to me.

[akashChopra1982]

Machine Learning leverages a lot of statistical tools from the 1960s. I think ML is amazing because we now have the computational power to run the computationally hungry stats algorithms from the 1960s. I think ML is gaining traction not because of something inherently good about ML (even though it's great), but because of an arms race among the FANG (Facebook, Apple, Netflix, Google) companies in the valley. Everyone now wants to have the next best ML tool. So there's an escalation in development. When I joined the workforce, regression was a big thing and Andrew Ng was God's prophet. Now we have ANN and CNN that process images from Lidars on self-driving cars. Andrew Ng is still big by the way. But now there are so many young players. They're blasting us oldies out of the water.