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This Subject is very wide and rather difficult for the students to collect suitable material for the Preparation of the subject from various numbers of books. An attempt has been made by us to provide the complete syllabus in a **Sirfpadhai.in**

The Engineers of the Letest Century are supposed to be more diversified in their knowledge. They are expected to be highly versatile in their compatibility.

By Keeping this view in our mind, We have prepared this Content to Make Engineering easy for students with easy language, which makes the subject more interesting.

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...

supervised learning in machine learningSupervised Learning:- The major motivation of supervised learning is to learn from past information. So what kind of past...

What is Human Learning?In cognitive science, learning is typically referred to as the process of gaining information through observation. And why do we need...

Write a short note on Convolutional Neural Networks.A convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied...

What do you mean by regularization? Explain.Regularization is a very important technique to prevent overfitting in machine learning problems. From a theoretical point of...

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...

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 distributionsWe have explored the idea of probability, we can consider the concept of a probability distribution. In situations where the variable being...

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 term training test and validation sets.Choosing the right dataset for a given classification task is of crucial importance for the generalization performance....