NEURAL NETWORKS & MACHINE LEARNING – MY DEFINITION
We used vast amount of Neural Networks and Machine Learning Codes to create our Algos for our predictive modeling and so many people have asked me to explain exactly what these two are. I have tried to summarize it below:
I need several pages to explain exactly what neural networks are, but in short, they are programs built to mimic the operation of neural networks inside the human brain. Studies have shown that building neural networks into machine learning algorithms is a highly effective way to improve their ability to solve complex problems, quickly.
Machine learning algorithms are growing in capability and availability every year, and they are doubtless the hottest and most promising tool related to both classification and prediction.
There are billions and billions of dollars wagered every year in the global sports betting market. As such, a machine learning algorithm that can predict the outcome of sporting events is massively profitable to anyone with the skillset to create one.Of course, there are lots of intrepid entrepreneurs out there doing exactly that.
Machine learning takes things a step further, applying artificial intelligence to algorithms. The application of machine learning produces a system with the ability to learn from experience and improve over time. A machine learning algorithm can both access and process the data it needs to make decisions, predict outcomes, and operate successfully without constant tweaks and manual input.
A machine learning algorithm is a technically artificial intelligence. Not only can it make independent decisions and predictions without any direct human involvement, but it’s also based upon something called “neural networks.”