Data analytics is the method of exploring raw data sets in order to find trends and draw conclusions about the information they contain. Across the globe companies are considering various analytic solutions to discover what will allow them to get the most out of their information. Let’s see the two main types of Data Analytics methods; DescriptiveContinue reading “Descriptive and Predictive Analytics”

# Category Archives: Machine Learning

## Moneyball : The Story Every Data Enthusiast Should Know

Moneyball is the story of general manager Billy Beane of Oakland A’s Baseball team. The story of attempting to create a baseball team on a low budget by employing data analysis to acquire new players. Moneyball Data Science Plot In 2001, Billy Beane’s Oakland A’s team lose to the Yankees( Baseball team) in the playoffsContinue reading “Moneyball : The Story Every Data Enthusiast Should Know”

## Machine Learning In Medicine

The world of medicine is changing due to the implementation of Artificial Intelligence. Fast improvement in computer science and availability of huge amount of data in the field of medicine makes machine learning system to tackle increasingly complex learning tasks, often with unbelievable success. The increasing focus of AI in medicine has led to someContinue reading “Machine Learning In Medicine”

## A brief Introduction to Probability Distribution for Machine Learning

Probability Distributions are prevalent in many fields, namely, computer science, stock market, astronomy and economics. In this blog we are going to see different probability distribution for Machine Learning and their properties. Also, we will discuss key statistical points for the simple models. Note, all the discussion in this blog is based on the assumptionContinue reading “A brief Introduction to Probability Distribution for Machine Learning”

## Evaluation Metric in Machine Learning

It is very important to check efficiency of the Machine Learning model. To check this, you have to evaluate the model based on some metric. But more important is a choice of metric to evaluate your machine learning model. Confusion Metric Confusion Metric is use to check the accuracy or correctness of your model. ItContinue reading “Evaluation Metric in Machine Learning”

## Decision Tree ; Explained

Decision tree is a non-parametric supervised machine learning algorithm, which can used for categorical as well as regression problem. It uses a tree structure to represent a number of possible decision paths and an outcome for each path. At each node, a question is asked and based on the answer of the question the pathContinue reading “Decision Tree ; Explained”

## A Complete guide to Linear Regression

Linear Regression is a supervised type of Machine Learning algorithm. It helps for predicting the continuous value. What is Regression ? When your output is not a categorical (like yes/no or 0/1) neither is cluster (like c0, c1, etc.), but instead is a continuous value (like temperature, height, etc.) is a Regression. Linear Regression algorithm helpsContinue reading “A Complete guide to Linear Regression”

## Logistic Regression in Brief

Logistic Regression is a Supervised Machine Learning Algorithm used for the classification problem. Now, you might wonder how regression can be used for classification problem. It works on the principle of Simple Linear Regression. Logistic Regression is taken from the field of statistics, where it is used to categorize the classes into true or false,Continue reading “Logistic Regression in Brief”