Free 100 Days of Data Science Master Classes - 💫 Machine Learning for Data Science- 18: SND Method & Z Score Calculation by @theiScale #datascience

🚀 Welcome to Day 18 of our Machine Learning series with @theiScale GitHub Link for Day 18 Notes: https://github.com/TheiScale/30_Days_Machine_Learning/tree/main/Day17 ✨ 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 18 of our 30 Days of Machine Learning Free Classes series! In today's session, we dive into the Z Score Technique, a powerful method for identifying outliers in datasets. Outliers are data points that deviate significantly from the rest of the data and can often distort analysis results. Understanding how to detect and handle outliers is crucial for robust data analysis and modeling. In this video, we start by introducing the concept of outliers and why they matter in data analysis and machine learning projects. We then walk you through the steps of applying the Z Score Technique, including calculating the Standard Normal Distribution (SND) method and Z score calculation. You'll learn how to: • Calculate the Mean and Standard Deviation of the dataset. • Compute the Z score for each data point using the formula: Z Score = (Data Point - Mean) / Standard Deviation. • Interpret Z scores and identify outliers based on predefined thresholds. • Apply the Z Score Technique to real-world datasets using Python programming language. Throughout the video, we provide clear explanations, practical examples, and Python code demonstrations to help you understand and implement the Z Score Technique effectively. By the end of this session, you'll have a solid understanding of how to detect and handle outliers using the Z Score Technique, empowering you to perform more robust data analysis and machine learning tasks. Don't forget to subscribe to our channel and turn on notifications to stay updated on upcoming sessions in our 30 Days of Machine Learning Free Classes series. Let's dive into the world of outliers and Z scores together! #outliers #dataanalysis #statistics #datascience #advantagesanddisadvantages #datavisualization #theiscale #iscale #datascience Don't miss out on any of our daily videos in this series! Subscribe now and hit the notification bell to stay updated. Let's master data analysis together!