Understanding Logistic Regression and Decision Tree Analysis

preview_player
Показать описание
🔥 Logistic Regression is a supervised machine-learning technique. It is used for predicting the categorical dependent variable using a given set of independent variables. Whereas, decision tree is also used in supervised types of machine learning and can be used to solve both regression and classification problems.

In this DataHour, Sanchita will explain the fundamentals of Logistic regression and will also demonstrate how to perform decision tree analysis.

🔥 Who is this DataHour for?
---- Students & Freshers who want to build a career in the Data-tech domain.
---- Working professionals who want to transition to the Data-tech domain.
---- Data science professionals who want to accelerate their career growth
---- Prerequisites: A strong interest in Data Science

🔥 About the Speaker
Sanchita is a Data Science and Analytics professional with hands-on experience in Data Analysis, statistics and econometrics. She is skilled in product analytics, predictive modeling and data visualization. She secured an executive programme in Data Science and decision science consulting degree from IIT Delhi after completing Bachelor's in Economics (Hons.) from Lady Shri Ram College for Women and Master's in Economics from Jawaharlal Nehru University.
Рекомендации по теме
Комментарии
Автор

Explained very well about the reason
Why logistic regression?

rajyalakshmikunda
Автор

how can i get this ppt material?>?\

naveedansari