This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

Three new books warn against turning into the person the algorithm thinks you are. Like a lot of Netflix subscribers, I find that my personal feed tends to be hit or miss. Usually more miss. The ...

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...

Tech companies acknowledge machine-learning algorithms can perpetuate discrimination and need improvement. By Zachary Small The artist Stephanie Dinkins has long been a pioneer in combining art and ...

Machine learning enables AI to learn and improve without direct programming. AI uses machine learning to analyze vast data sets and identify patterns. Accuracy of AI predictions depends on quality ...