Machine learning, deep learning, AI .. buzz words these days, but are they really ?
According to techtarget website, Machine learning was first conceived from the mathematical modeling of neural networks. A paper by logician Walter Pitts and neuroscientist Warren McCulloch, published in 1943, attempted to mathematically map out thought processes and decision making in human cognition.
This is a tutorial I created to show you how we can predict rainfall based on data from Austin weather center.
The code and data can be found here => https://github.com/BekBrace/Machine.Learning.Rainfall.Prediction
In 1950, Alan Turning proposed the Turing Test, which became the litmus test for which machines were deemed "intelligent" or "unintelligent." The criteria for a machine to receive status as an "intelligent" machine, was for it to have the ability to convince a human being that it, the machine, was also a human being. Soon after, a summer research program at Dartmouth College became the official birthplace of AI.
From this point on, "intelligent" machine learning algorithms and computer programs started to appear, doing everything from planning travel routes for salespeople, to playing board games with humans such as checkers and tic-tac-toe.
The way I see it, Machine learning is like an ocean and we are still on the shore, I mean by time the progress will be big and the effect will be universal not only in the algorithms we write in Python or JavaScript to automate / to train / test / predict ..etc but actually machine learning will be very effective in medicine, education, engineering and other fields as well.
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