In the last few years, machine learning has become one of the most important and prolific IT and artificial intelligence branches. It's not surprising that its applications are becoming more widespread day by day in every business sector, always with new and more powerful tools and results. Open source, production-ready frameworks, together with hundreds of papers published every month, are contributing to one of the most pervasive democratization processes in IT history. But why is machine learning so important and valuable?
In this chapter, we are going to discuss the following:
- The difference between classic systems and adaptive ones
- The general concept of learning, proving a few examples of different approaches
- Why bio-inspired systems and computational neuroscience allowed a dramatic improvement in performances
- The relationship between big data and machine learning
