Understanding Machine Learning: From Theory to Algorithms

Understanding Machine Learning: From Theory to Algorithms 

Shai Shalev-Shwartz

Preference :

The term machine learning refers to the automated detection of meaningful patterns in data. In the past couple of decades, it has become a common tool in almost any task that requires information extraction from large data sets. We are surrounded by a machine learning-based technology: Search engines learn how to bring us the best results (while placing profitable ads), antispam software learns to filter our email messages, and credit card transactions are secured by software that learns how to detect frauds. Digital cameras learn to detect faces and intelligent personal assistance applications on smart-phones learn to recognize voice commands. Cars are equipped with accident prevention systems that are built using machine learning algorithms. Machine learning is also widely used in scientific applications such as bioinformatics, medicine, and astronomy.

Content :
  • Introduction
  • Foundations
  • From Theory to Algorithms
  • Additional Learning Models
  • Advanced Theory
  • Appendix A Technical Lemmas
  • Appendix B Measure Concentration

Download Understanding Machine Learning: From Theory to Algorithms free PDF


Share this

Related Posts

Next Post »