Discover Supervised Learning Course
Welcome to Discover Supervised Learning's Online training with live Instructor using an interactive cloud desktop environment DaDesktop.
Experience remote live training using an interactive, remote desktop led by a human being!
This instructor-led live training is designed to provide participants to gain mastery on discover supervised learning. You will learn the fundamentals of discover supervised learning and with greater emphasis on the functionality and application to your work or study.
Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs. It infers a function from labeled training data consisting of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and the desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way.
- Algorithm choice
- Bias-variance tradeoff
- Function complexity and amount of training data
- The dimensionality of the input space
- Noise in the output values
- Other factors to consider
- How supervised learning algorithms work
- Empirical risk minimization
- Structural risk minimization
- Generative training
- Approaches and algorithms
Course Category: Programming II