Chasing Genius

ML | PREDICTING PRICE OF PRE-OWNED CARS In this article we are going to discuss a practical application of machine learning using a case study on Linear Regression. Linear Regression is a supervised learning algorithm. It is used to predict the real- valued output y based on the given input value x. it depicts the relationship between the dependent variable y and the independent variable x. Let’s look at the problem statement: Strom Motors is an e-commerce company who act as mediators between parties interested in selling and buying pre-owned cars. Storm Motors wishes to develop an algorithm to predict the price of the cars based on various attributes associated with the car. we have downloaded the dataset for this problem statement from kaggle.com. Kaggle is an online community devoted to Data Science and Machine Learning founded by Google in 2010. The dataset is named as CAR DETAILS FROM CAR DEKHO.csv. The dataset can be found here. Data Cleaning Let us understand th...

Salary Prediction Web App In this article, we are going to discuss how to predict the salary based on various attributes related to salary  using Random Forest Regression. This study focuses on a system that predicts the salary of a candidate based on candidate’s qualifications, historical data, and work experience. This app uses a machine learning algorithm to give the result. The algorithm used is Random Forest Regression. In this problem, the target variable (or output), y, takes value of salary for a given set of input features (or inputs), X. The dataset contains gender, secondary school percentage, higher secondary school percentage, higher secondary school stream, degree percentage, degree type, work experience and specialization of candidate. Below is the step-by-step Approach: Step 1: Import the necessary modules and read the dataset we are going to use for this analysis. Below is a screenshot of the dataset we used in our analysis. Step 2: Now before moving ...