Reinforcement learning is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize cumulative reward. This post includes the course notes of reinforcement learning course by Andrew Ng.
A recommender system is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user. This post includes the course notes of recommender system course by Andrew Ng.
Unsupervised learning is a type of algorithm that learns patterns or data groupings from unlabeled data without the need for human intervention. This post includes the course notes of unsupervised learning course by Andrew Ng.
Decision trees are decision support hierarchical model that use tree model to make judgment or decision. Decision trees are commonly used in decision analysis, but are also a popular tool in machine learning.
When building a machine learning system, there are actually a series of processes, namely, the full cycle of the machine learning project. Training models is just one step of the cycle.
Machine learning diagnostic is a test that you run to gain insight into what is/isn't working with a learning algorithm and to gain guidance into improving its performance.
Neural network, which is also called artificial neural networks (ANNs) or neural networks (NNs) is an advanced model in machine learning. This post includes the course notes of neural network course by Andrew Ng.
Supervised learning is the most commonly used type of machine learning. This post includes the course notes of supervised learning course by Andrew Ng.
Machine learning is a broad subfield of artifial intelligence. This post includes the course notes of machine learning introduction course by Andrew Ng.
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