## Logistic regression algorithm from scratch In python(Using Numpy only)

Logistic Regression is simple and easy but one of the widely used binary classification algorithm in the field of machine

## Breast cancer prediction using Logistic Regression Algorithm

Logistic Regression is simple and easy but one of the widely used binary classification algorithm in the field of machine

## What is F1-score and what is it’s importance in Machine learning?

F1-Score or F-measure is an evaluation metric for a classification defined as harmonic mean of precision and recall. It is

## The Logistic Regression Algorithm-Detailed overview

What is Logistic Regression? Logistic Regression is one of the most widely used binary classification algorithm in the field of

## How to select machine learning algorithm for your problem?

Selecting a suitable machine learning algorithm for your problem can be a difficult task. If you have a lot time,

## Hyperparameters vs. Parameters

What are Hyperparameters? A hyperparameter is a entities of a learning algorithm, usually (but not always) having a finite numerical

## What is Ensemble Learning?

The basic supervised machine learning algorithms like KNN, Decision trees, etc. have certain limitations. Because of their simplicity, sometimes they

## Implementataion of Naive Bayes in python(using Sklearn)

Naive Bayes Classifier is a classification algorithm based on Bayes’ Theorem of probability. It is based on the principle that

## What is confusion matrix?

Confusion matrix is a table that is used to measure the performance of the machine learning classification model(typically for supervised learning, in case of unsupervised learning it usually called matching matrix) where output can be two or more classes. Each row of the confusion matrix represents the instances in a predicted class while each column represents the instance in an actual class or vice versa.

## Basic concepts of K-means Clustering

k-Means Clustering: A Centroid-Based Technique K-means clustering is one of the easiest, simple and most popular unsupervised machine learning algorithms.

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