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

Neural Network

Neural Network Artificial neural network is the predictive model. Artificial Neural network in machine learning is inspiration for human brain and how it works. Our brain consists of the collection of neurons wired together. Every neuron connected to each other takes output from previous neurons that feed into it, does the calculation and then either … Continue reading Neural Network

Advance Gradient Descent

In Simple BGD (Batch Gradient Descent) the parameters are updated by some of all the square error of data set. However, BGD convergence much accurately but when there are large data set then the convergence will take lot of time and memory. Therefore, to overcome these problems, following evolution were made on optimizing parameters. Stochastic … Continue reading Advance Gradient Descent

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