Course Hive
Search

Welcome

Sign in or create your account

Continue with Google
or
💫 Machine Learning for Data Science - 12: Categorical Data Imputation by @theiScale #theiscale
Play lesson

Free 100 Days of Data Science Master Classes - 💫 Machine Learning for Data Science - 12: Categorical Data Imputation by @theiScale #theiscale

4.0 (0)
14 learners

What you'll learn

This course includes

  • 91.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

Summary

Full Transcript

🚀 Welcome to Day 12 of our Machine Learning series with @theiScale GitHub Link for Day 12 Notes: https://github.com/TheiScale/30_Days_Machine_Learning/tree/main/Day%201%20ML ✨ Kickstart your career as a Data Analyst. Apply today! - https://www.theiscale.com/DataAnalytic?analytics=13 ❇️ Explore our Job Oriented Courses: https://www.theiscale.com/explore-course ➖➖➖➖➖➖ 📱 For Any Further Queries or Doubts? Contact- 7880-113-112 (Student Helpline Number) For any query connect in WhatsApp with us: https://wa.me/917880113112 ➖➖➖➖➖➖ ✳️ Join Telegram Channel- https://t.me/TheiScale ✳️ Join WhatsApp Channel- https://whatsapp.com/channel/0029VaB5ekEKQuJQV572vi2c ➖➖➖➖➖➖➖ 🔗 Download App Google Play: https://play.google.com/store/apps/details?id=com.logixhunt.ihhpet&pli=1 Welcome to Day 12 of "30 Days of Machine Learning for Data Science" by The iScale! In today's session, we explore Categorical Data Imputation techniques, focusing on Mode and Most Frequent strategies. Key topics covered include: - Understanding the purpose and significance of using "Mode" in categorical data imputation. - Explaining Most Frequent Imputation and its application in handling missing values. - Identifying the types of variables suitable for mode/most frequent imputation. - Discussing scenarios and criteria for selecting mode/most frequent category imputation over other methods. - Practical insights into missing value imputation using mode and most frequent techniques. Join us as we dive deep into the world of categorical data imputation and learn essential strategies to effectively handle missing values. Whether you're a beginner or an experienced data scientist, understanding these techniques is crucial for robust data analysis and modeling. Don't let missing data hinder your analysis—learn how to leverage univariate imputation techniques to enhance the quality and reliability of your results. Watch now to expand your knowledge and elevate your data analysis skills! Watch now @theiScale to deepen your understanding and improve your data analysis skills! #theiscale #iscale #datascience #dataanalytics #machinelearning #machinelearningbasics #machinelearningfullcourse #viral #career #job #dataanalysis

Course Hive

Continue this lesson in the app

Install CourseHive on Android or iOS to keep learning while you move.

Related Courses

FAQs

Course Hive
Download CourseHive
Keep learning anywhere