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  • Courseware 
    CS229 - Machine Learning

    CS229 - Machine Learning

    This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.

    Subjects:
    Computing
    Keywords:
    Pattern perception -- Statistical methods Machine learning
    Resource Type:
    Courseware
     
  • Courseware 
    User Interface Design and Implementation

    User Interface Design and Implementation

    This course examines human-computer interaction in the context of graphical user interfaces. The course covers human capabilities, design principles, prototyping techniques, evaluation techniques, and the implementation of graphical user interfaces. Deliverables include short programming assignments and a semester-long group project. Students taking the graduate version also have readings from current literature and additional assignments.

    Subjects:
    Computing
    Keywords:
    Human-computer interaction User interfaces (Computer systems)
    Resource Type:
    Courseware
     
  • Courseware 
    Artificial Intelligence

    Artificial Intelligence

    This course includes interactive demonstrations which are intended to stimulate interest and to help students gain intuition about how artificial intelligence methods work under a variety of circumstances.

    Subjects:
    Computing
    Keywords:
    Artificial intelligence
    Resource Type:
    Courseware