Machine learning is the application of Artificial Intelligence that dispenses systems the ability to automatically learn, think and improve from experience without being certainly programmed. Machine learning kingpins on the development of computer programs that can outbursts data and use it learn for themselves.
Machine Learning brutalize analytical model building. It uses methods from Statistics, operation research and physics and neural networks to find hidden insights in data without explicitly being programmed for what to look or where to conclude. The main aim is to allow computers to learn automatically without human intervention and adjust actions accordingly.
Machine learning warrants survey of massive quantities of data. While it generally delivers faster, more exact results in order to recognize dangerous risk or beneficial opportunities, it may also require additional time and resources to train it properly. Merging machine learning with cognitive technologies and AI can make it even more productive in managing large volumes of information.
- Track 1-1 Machine learning and statistics
- Track 2-2 Machine learning tools and techniques
- Track 3-3 Fielded applications
- Track 4-4 Generalization as search
- Track 5-5 Machine Translation