Why Is Machine Learning so Important? 🦾
We are in the midst of a revolution provided by Big Data. According to recent estimates, about 2.5 quintillion bytes are generated per day across the planet, and much of this data produced is not being effectively used because of the limited human capacity to analyze this exponential flood of data.
Much of this data and its relationships is beyond our power of understanding, that is, someone or something needs to do the work for us. That’s exactly why Machine Learning is becoming increasingly popular.
For the first time in history we have a lot of data available and processing capacity, which allows us to explore this data without the need for human intervention — we train an algorithm, we build the model and from there it will do the work for us.
Considering a career in Machine Learning and learning everything possible on this subject is one of the smartest decisions we can make in our professional career. Soon, Machine Learning will be present in all business areas and in all activities of our lives. The professionals who know how to work with these technologies will certainly be the creators of this new world.
Companies such as Google, Facebook, Amazon, Apple, IBM, Microsoft, or the world’s technology giants that invest billions of dollars in research and development, are devoting their efforts to increasingly offering machine learning-based solutions.
There are so many new possibilities brought by Machine Learning that we will soon be dependent on Machine Learning in the same way that we are already dependent on computers and the internet.
Autonomous cars, the internet of things, machine learning — technology is increasingly advancing and the future not so far away, predicts computers that act and react like humans. This is the proposal of cognivite computing — intelligent machines that learn behaviors, languages and regionalisms to be able to interact according to what they can interpret from the speech of their human interlocutors.
This artifact is especially strong in a market in which more and more consumers expect to be better served and preferably in a short period of time. Cognitive computing is based on machine learning concepts, so they are not concepts of a distant reality. Companies are already using cognitive computing solutions.
The Machine Learning process begins in defining a business problem, using specific libraries such as scikit-learn — the main Python library for machine learning, the routine process of collecting, exploratory analysis and data preprocessing, selecting variables for model performance improvement, and choosing for algorithms within a wide range of classification algorithms, regression or ensemble algorithms — for more complex solutions.