Learn how to reproduce human learning on machines, that’s Machine Learning.

Today, as a data scientist, you can build systems that crunch data through complex algorithms — all at low cost and high processing capacity. Machine Learning algorithms are at the heart of the transformations we are currently experiencing.

We’re living in the age of data abundance and using algorithms that are able to extract precious information from that data is the chance to turn raw data into knowledge — knowledge is power.

With the large number of open-source libraries available today, it’s the opportunity for those who want to help transform the world and help predict events — well before they occur and make better decisions.

We’re going through what they call a perfect storm. We now have a large volume of data generated with high variability and high speed — exactly the definition of Big Data. We have algorithms capable of learning from data along with a lot of processing power available, all this leads us to a real revolution in human activities.

Much of what we have in Machine Learning today has existed for a few decades, statistical and mathematical techniques have existed for a long time, but never in human history have we had so much data and computational ability to extract useful knowledge, or information that we even imagine exists.

One of the components in the midst of all this storm is the Machine Learning Algorithm — a small piece of software that contains code capable of programming computers so that they can do certain actions on their own. Using Machine Learning, we train a specific algorithm by ingesting data, it will find the patterns and create a piece of software — a predictive model. Once the predictive model is created, we present new data to this model and it will be able to make new predictions as we ingest data.

That is, if we had to build a program on our own to make these predictions, we would have a lot of work and probably couldn’t get a good result — with Machine Learning we are able to do this practically automatically, although there is a lot of work in data preprocessing.

#machine-learning #data-science #algorithms #artificial-intelligence