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 ...

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 ...

Machine learning algorithms generate predictions, recommendations and new content by analyzing and identifying patterns in their training data. These capabilities power widely used technologies such ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

What is boosting in machine learning? Boosting in machine learning is a technique for training a collection of machine learning algorithms to work better together to increase accuracy, reduce bias and ...

Overview: Recommends a core stack of seven tools, with other platforms treated as optional based on the learner's needsNames ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

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 ...