Handling Imbalanced Dataset in Machine Learning: Easy Explanation for Data Science Interviews скачать в хорошем качестве

Handling Imbalanced Dataset in Machine Learning: Easy Explanation for Data Science Interviews

Imbalanced Data is one of the most common machine learning problems you’ll come across in data science interviews. In this video, I cover what an imbalanced dataset is, what disadvantages it presents, and how to deal with imbalanced data when data contains only 1% of the minority class. 🟢Get all my free data science interview resources https://www.emmading.com/resources 🟡 Product Case Interview Cheatsheet https://www.emmading.com/product-case... 🟠 Statistics Interview Cheatsheet https://www.emmading.com/statistics-i... 🟣 Behavioral Interview Cheatsheet https://www.emmading.com/behavioral-i... 🔵 Data Science Resume Checklist https://www.emmading.com/data-science... ✅ We work with Experienced Data Scientists to help them land their next dream jobs. Apply now: https://www.emmading.com/coaching // Comment Got any questions? Something to add? Write a comment below to chat. // Let's connect on LinkedIn:   / emmading001   ==================== Contents of this video: ==================== 00:00 Introduction 01:20 Interview Questions 01:38 Imbalanced Data 03:15 Why it causes problems? 04:27 How to deal with imbalanced data? 08:13 Model-level methods 11:33 Evaluation Metrics 13:25 Outro