Ads
related to: learning log sample- About Articulate
Learn more about why Articulate
is loved by 122 million learners.
- Articulate 360
Create courses for your
learning management system.
- About Articulate
amazon.com has been visited by 1M+ users in the past month
Search results
Results from the Health.Zone Content Network
Learning log. Two students share and compare their learning logs. Learning Logs are a personalized learning resource for children. In the learning logs, the children record their responses to learning challenges set by their teachers. Each log is a unique record of the child's thinking and learning. The logs are usually a visually oriented ...
Rademacher complexity. In computational learning theory ( machine learning and theory of computation ), Rademacher complexity, named after Hans Rademacher, measures richness of a class of sets with respect to a probability distribution. The concept can also be extended to real valued functions.
v. t. e. Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable can take a discrete set of values are called ...
In machine learning and mathematical optimization, loss functions for classification are computationally feasible loss functions representing the price paid for inaccuracy of predictions in classification problems (problems of identifying which category a particular observation belongs to). [1] Given as the space of all possible inputs (usually ...
Learning with humans. Model diagnostics. Mathematical foundations. Machine-learning venues. Related articles. v. t. e. A large language model ( LLM) is a computational model notable for its ability to achieve general-purpose language generation and other natural language processing tasks such as classification.
Supervised learning. Supervised learning ( SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. [1]
In mathematics, the logarithm is the inverse function to exponentiation. That means that the logarithm of a number x to the base b is the exponent to which b must be raised to produce x. For example, since 1000 = 103, the logarithm base of 1000 is 3, or log10 (1000) = 3.
Maximum likelihood estimation. In statistics, maximum likelihood estimation ( MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable.
Ads
related to: learning log sampleamazon.com has been visited by 1M+ users in the past month