Tag: Data Science
Data Science is a hot topic in today’s for prediction and future world
Erosion of an Image Using OpenCV-Python
Last updated on 10th June 2021 by [email protected] | Category: Data Science & ML, Machine Learning
Hi there, today we will be talking about something interesting as well as simple : Erosion of an Image Using OpenCV module in Python. An image has many features (for example:- edge, contrast etc.). Erosion is one of the fundamental operations in morphological image processing. This operation basically erodes away the boundaries of foreground object. […]
Creating a Decision Tree using the ID3 Algorithm
Last updated on 30th May 2021 by [email protected] | Category: Data Science & ML, Machine Learning
We have often used decision tree algorithm for classification in our Machine Learning Model. But have you ever think about how this decision tree works or what is the algorithm behind it? In this blog, we will be Creating a Decision Tree using the ID3 algorithm, which is one of the algorithms used to create […]
Linear Regression Machine Learning Project for House Price Prediction
Last updated on 27th November 2021 by H Sayyed | Category: Data Science & ML, Machine Learning
In this tutorial, you will learn how to create a Machine Learning Linear Regression Model using Python. You will be analyzing a house price predication dataset for finding out the price of a house on different parameters. You will do Exploratory Data Analysis, split the training and testing data, Model Evaluation and Predictions. What is […]
Kaggle Titanic Python Competiton Getting Started
Last updated on 27th November 2021 by H Sayyed | Category: Data Science & ML
This tutorial explains how to get started with your first competition on Kaggle. Titanic machine learning from disaster. We will be getting started with Titanic: Machine Learning from Disaster Competition. With this project, you’ll get familiar with Machine Learning Python Basics and also learn Kaggle platform functionalities. About the challenge – Titanic: ML from Disaster […]
