## Naives Bayes Classifier

Naive Bayes is the method of supervised learning. It is a classification algorithm which is used to predict the class of  a given data points. Naive Bayes is based on Bayes Theorem in which the probability of event which is based on previous knowledge and event. Example: If the vehicles is long width and high height then … Continue reading Naives Bayes Classifier

## K-Mean Clustering

In my opinion, K-Means are often confused with K-Nearest Neighbor. KNN is a classification algorithm, in which given x is classified by the kth nearest neighbor. The majority of nearest neighbor with x is classified into that cluster groups. Whereas, K-Means are centroid based clustering algorithms. These algorithms lies in the category of unsupervised learning. … Continue reading K-Mean Clustering

## Gradient Descent and Cost Functions

When talking about linear regression(only one variable) then the hypothesis is ℎ𝜃 (𝑥) = 𝜃0 + 𝜃1𝑥 where hypothesis is best fitting line for the data. In this equation, guessing theta values that creates the best fit line for our linear regression model is important. Therefore to determine the theta values in the equation, there … Continue reading Gradient Descent and Cost Functions

## Steps for Machine Learning project

I read a blog online know about how data scientist accomplish their projects on machine learning or artificial intelligence. I found that the most important things for data scientist is to gather data and to know about the data. First thing first, you should know what type of problem you want to solve therefore first … Continue reading Steps for Machine Learning project