Probability Density Function – Machine learning
What do you mean by probability density function?In a discrete random variable, probabilities are associated with particular individual values of the random variable, and...
What is the CNN architecture in machine learning?
What is the CNN architecture in machine learning?CNNs are widely used in different fields, such as image recognition, classification, and vision in computers, in...
regularization and weight regularization in machine learning
regularization and weight regularization in machine learningRegularization in machine learning helps prevent a model from overfitting by discouraging it from learning overly complex patterns....
Support Vector Machine(SVM)
Support Vector MachineSupport vector machines are supervised learning models with associated learning algorithms that analyze data after which they are used for classification. Classification...
Probability distributions |Discrete probability distribution
Probability distributionsWe have explored the idea of probability, we can consider the concept of a probability distribution. In situations where the variable being...
Define some examples of linear algebra in machine learning.
Define some examples of linear algebra in machine learning.Some examples of linear algebra in machine learning are as follows-Linear regressionRegularizationPrincipal component analysis (PCA)Singular-value decomposition...
Batch Normalization | Write down the properties of batch normalization.
Batch NormalizationWhat do you understand by batch normalization? Explain.Batch normalization is a recently popularized method for accelerating deep network training by making data standardization...
Bayesian classifiers |Naive Bayes classifiers
What are Bayesian classifiers?Bayesian classifiers are statistical classifiers. They can predict class membership probabilities, such as the probability that a given tuple belongs to...
Explain the working of backpropagation neural networks with neat architecture and flowchart.
Architecture of backpropagation networkA back propagation neural network is a multilayer, feedforward neural network. It is made up of an input layer, a hidden...
Explain the term training test and validation sets.
Explain the term training test and validation sets.Choosing the right dataset for a given classification task is of crucial importance for the generalization performance....
