Objectives

• How to use Classification in machine learning to identify the category of a given dataset, and these algorithms are mainly used to predict the output for the categorical data.How to use Clustering in machine learning to identify groups of similar objects in datasets with two or more variable quantities• how to study your data to extract meaningful insights for business• How to use Classification in machine learning to identify the category of a given dataset, and these algorithms are mainly used to predict the output for the categorical data.• How to use Clustering in machine learning to identify groups of similar objects in datasets with two or more variable quantities

Outcomes

• Make accurate predictions.• Make precise data forecasts.• Make powerful analyses for data.• Extract meaningful insights for business from data.• Have a strong understanding of many Machine Learning algorithms.• Make powerful analysis.• Add significant worth to your business.• Create strong added value to your business.• Employ Machine Learning for personal gain.• Know which Machine Learning model to choose for each type of problem.• Build an army of powerful Machine Learning models and know how to combine them to solve any problem.

Course Contents

• How to predict the correct label of a given input data using classification• Types of classification:o Logistic Regressiono K-NN, SVMo Kernel SVMo Naive Bayeso Decision Tree Classificationo Random Forest Classification• How to evaluate and select best model for our data • Performance analysis • How to organize similar objects into groups within a machine learning algorithm using clustering• Types of classification:o K-Meanso Hierarchical Clustering• How to evaluate and select best model for our data • Performance analysis

Description

Data will be available soon!