## Standardization and Normalization in Machine Learning

In this post you will learn about Normalization and Standardization in machine learning.You will also learn why it is important and why and how to use Normalization and Standardization in Machine Learning in Python. Why to Normalize or Standardize? Sometimes,features of our dataset may have different scales.For example,One feature may… Continue reading

## Evaluation Metrics for Classification Models

Evaluating performance of machine learning models is a crucial task of model building process.When you finished building the model,you need the perform some analysis on the performance of model to check whether you model will do best in real world. In this post,you will learn about how to evaluate performance… Continue reading

## Evaluating Regression models with python scikit-learn

In this guide,you will learn how to evaluate Regression models with various metrics like Root Mean Square Error(RMSE), Mean Absolute Error(MAE) ,Mean Square Error(MSE),R-Squared Score and Adjusted R-squared Score. Let’s first implement our regression model then,we will evaluate it using rmse ,mse,mae,r-square and adjusted r-squared metrics.If you want to know… Continue reading

## Logistic Regression–A detailed explanation with scikit-learn Implementation

This guide will give you a brief and detailed explanation of Logistic Regression and Multinobial logistic regression.You will also learn how to implement Logistic Regression and Multinobial Logistic Regression with scikit-learn. What is Logistic Regression? Logistic Regression is a statistical method for predicting for predicting a dependent variable given a… Continue reading

## Simple and Multiple Linear Regression –Detailed Explanation with Scikit-learn Implementation

This tutorial will give you a brief and detailed understanding of Simple and Multiple Linear Regression concept.I will be also showing you how to implement Simple and Multiple linear regression using scikit-learn. What is Linear Regression? Linear Regression is a statistical method which consists of one or more independent variable… Continue reading

## Linear and Logistic Regression with Pythons Statsmodels

In this tutorial I am going to explain you the importance of statsmodels api and show you how you can implement Linear and Logistic Regression using Statsmodels and start analysis of the model performance.So,lets dive in… What is Statsmodels and why to use it? Statsmodels is a Python module that… Continue reading

## What is Dummy variable and Dummy variable trap?

Hello and Welcome to this tutorials. In this tutorial,I am going to explain concept of dummy variables,dummy variable trap ,how to deal with these problem and how to use pandas get_dummies() to implement one-hot-encoding method to solve this problem. Note: One-hot-Encoding is achieved in pandas by using pandas get_dummies() method…. Continue reading

## 6 Different ways to create DataFrame in Pandas.

Data Science or data Analytics is a process of analysing large set of data points to get answers on questions related to that data set. Now,if you have been following data science or analytics or practising it,you might have heard of or have used pandas. PANDAS-Introduction Pandas is a high-level… Continue reading