## Random Forest on Titanic Dataset | Predicting Survival

In this chapter we will be using Random Forest on Titanic Dataset. Titanic is one of the most widely used datasets on Kaggle. This dataset …

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## Random Forest on Titanic Dataset | Predicting Survival

## Random Forest Classifier – Forest of Multiple Decision Trees

## k Means Clustering From Scratch in Python

## k Means Algorithm Complete Step by Step Guide

## Understanding Math for Support Vector Machine (SVM)

## Bias Variance Trade-off in ML; Introduction for Beginners

## Naïve Bayes Algorithm for Multiple Features

## Learning Naïve Bayes Machine Learning Algorithm

## Dog Cat Classification Using k Nearest Neighbor Algorithm

## How k Nearest Neighbor Algorithm Works?

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In this chapter we will be using Random Forest on Titanic Dataset. Titanic is one of the most widely used datasets on Kaggle. This dataset …

In order to understand the working of Random Forest Classifier, it is important to have knowledge of Decision tree classifier. Consider following decision tree; How …

We have completely understand the working of k Means Clustering; Unsupervised Machine Learning Algorithm. Take same data from there. We have a data set of …

k-Means algorithm (clustering) is a method of vector quantization, originally from the field of signal processing, whose objective is to partition “N” instances / records …

Support Vector Machine (SVM) is one of the Machine Learning Algorithms which is primarily used for classification problems but also for regression problems. This algorithm …

In order to understand Bias Variance Trade-off in Machine Learning, let’s understand how machine learning algorithm generate pattern. Pattern is generated from training data and …

Naïve Bayes Algorithm, most powerful Machine Learning Algorithm used for predictive modeling based on Bayes Theorem. Naïve Bayes Algorithm has feature independence assumption and very …

Naïve Bayes is one of the simple but most powerful Machine Learning Algorithm used for predictive modeling and analytics based on Bayes Theorem. Before learning …

In Machine Learning the k nearest neighbor algorithm (k-NN) is a non-parametric technique, used for classification and regression problems. Input to k-NN consists of the k closest training examples and query (value we …

In Machine Learning (also known as Pattern Recognition), the k nearest neighbor algorithm (k-NN) is a non-parametric technique developed by Thomas Cover used for classification and regression problems. Input to k-NN consists …