muhil17

Spam Detection using Multinomial Naive Bayes

Welcome to the Spam Detection using Multinomial Naive Bayes post. I hope you have gone through all the previous posts on Machine Learning, Supervised Learning and Unsupervised Learning. Spam Detection Whenever you submit details about your email or contact number on any platform, it has become easy for those platforms to market their products byContinue reading “Spam Detection using Multinomial Naive Bayes”

Principal Component Analysis

Welcome to the Principal Component Analysis (PCA) post. I hope you have gone through all the previous posts on Machine Learning, Supervised Learning and Unsupervised Learning. Principal Component Analysis is an unsupervised learning algorithm that is used for the dimensionality reduction in machine learning. PCA is a dimensionality-reduction method that is often used to reduce the dimensionality ofContinue reading “Principal Component Analysis”

Correlation vs Covariance

Welcome to the Correlation vs Covariance post. I hope you have gone through all the previous posts on Machine Learning, Supervised Learning and Unsupervised Learning. In Statistics and Machine Learning, frequently we come across these two terms known as Covariance and Correlation. The two terms are often used interchangeably. These two ideas are similar, but not theContinue reading “Correlation vs Covariance “

Standard Deviation vs Variance

Welcome to the Standard Deviation vs Variance post. I hope you have gone through all the previous posts on Machine Learning, Supervised Learning and Unsupervised Learning. Standard Deviation: Standard deviation is a measure of the amount of variation or dispersion of a set of values. It measures the Spread of a group of numbers fromContinue reading “Standard Deviation vs Variance”

Unsupervised Learning (Part 1)

Welcome to the Unsupervised Machine Learning post. I hope you have gone through the previous posts on Machine Learning and Supervised Learning. If no, kindly go through those posts before starting from here for a better understanding. We have seen the various types of ML in the Part 1 of Machine Learning post. So in this postContinue reading “Unsupervised Learning (Part 1)”

Supervised Learning (Part 4)

Welcome to the Part 4 of Supervised Machine Learning post. I hope you have gone through the previous posts on Machine Learning and Supervised Learning Part 1, Part 2 and Part 3. If no, kindly go through those before starting from here. In this post we are going to see about the various applications of supervisedContinue reading “Supervised Learning (Part 4)”

Supervised Learning (Part 3)

Welcome to the Part 3 of Supervised Machine Learning post. I hope you have gone through the previous posts on Machine Learning and Supervised Learning Part 1 and Part 2. If no, kindly go through those before starting from here. In this post we are going to see about the various algorithms of supervised machine learningContinue reading “Supervised Learning (Part 3)”

Supervised Learning (Part 2)

Welcome to the Part 2 of Supervised Machine Learning post. I hope you have gone through the previous posts on Machine Learning and Supervised Learning. If no, kindly go through those before starting from here. In this post we are going to see about the types of supervised learning with examples and their applications. So letContinue reading “Supervised Learning (Part 2)”

Supervised Learning

PART 1 Welcome to the Supervised Machine Learning post. I hope you have gone through the previous posts on Machine Learning. If no, kindly go through those posts before starting from here. We have seen the various types of ML in the Part 1 of Machine Learning post. So in this post we are goingContinue reading “Supervised Learning”

Machine Learning (Part 2)

Welcome to the Part 2 of Machine Learning. If you haven’t gone through the Part 1 of ML click here Part-1. In this post we are going to discuss about the core statistics which helps in understanding ML. Machine Learning is nothing but the combination of statistics with other fields. So in order to clearlyContinue reading “Machine Learning (Part 2)”