## Support Vector Machines

SVM or large margin classifier are similar to other machine learning classification algorithm such as logistic regression. It is defined as given the labeled data, the algorithm find the optimal plane to categorizes. Other algorithms such as Neural Network and Logistic regression, SVM gives clear view of learning for non-linear function. Logistic regression (sigmod function) … Continue reading Support Vector Machines

## Recommendation System

The most essential way to grow the businesses and make more customers more satisfied with the services. It is very important to understand the needs and interest of the customers. The recommendation system are developed in order to know about the customers and thus offer products or services to the customers accordingly. These recommendation systems … Continue reading Recommendation System

## Decision Tree

When learning about Decision tree, I learned about Entropy. In my opinion, entropy is important to learn for data science and in decision tree. In simple words, entropy is the measurement of level of impurity in the data set or it is measurement of uncertainty. It is defined as Entropy = – p(a)*log(p(a)) – p(b)*log(p(b)) The … Continue reading Decision Tree

## Logistic Regression

Logistic regression is a statistical model, in which analyzing one or more independent variables with the possible outcome. The outcome is measure with a dichotomous(separate line) variable. In logistic regression, the outcome is binary for example if cancer is benign then True/0 or if maligned then False/1 Logistic regression goal is to find the best … Continue reading Logistic Regression

## Machine Learning: Regression

Regression in statistics is defined as estimating the relationship among variables. It is defined as to determine the strength of relationship with dependent variable (Y) and change in variables (independent variables (X)). It is to used for financial data, stock market data and business analysis. It helps to understand the relationship between variables(data) generated. For … Continue reading Machine Learning: Regression

## 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