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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 
    CS223A - Introduction to Robotics

    CS223A - Introduction to Robotics

    The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of relevant results from geometry, kinematics, statics, dynamics, and control. The course is presented in a standard format of lectures, readings and problem sets.

    Subjects:
    Mechanical Engineering
    Keywords:
    Robotics
    Resource Type:
    Courseware