Скачать или смотреть Probability: Conditional Probability | Bayes' Theorem | Discrete & Continuous | Independent Events

📘 Notes: https://robosathi.com/docs/maths/prob...

This video covers Probability — a fundamental concept for Machine Learning & Data Science. Learn step-by-step with clear examples and intuitive explanations.

Pre-Requisites
✅    • Random Variable | Discrete & Continuous | ...  

Learning Objectives:-

✅ Why probability matters and its uses
✅ Sample Space & Events: defining outcomes and events
✅ Discrete vs Continuous Probability: understanding different types of events
✅ Conditional Probability: updating probabilities with new information
✅ Law of Total Probability: combining multiple events
✅ Bayes Theorem: updating beliefs using evidence
✅ Independence of Events: simplifying calculations when events are unrelated


🕘 Time Stamp 🕔

00:00:00 Intro
00:03:11 Probability
00:08:55 Sample space
00:12:25 Discrete & Continuous
00:18:02 Mutually Exclusive & Independent Event
00:34:34 Conditional Probability
00:43:48 Bayes' Theorem
00:52:54 Bayes' Theorem Generalised Form
00:59:17 Law of Total Probability
01:08:00 Independence of Events
01:30:25 Summary

By the end of this video, you’ll have a clear understanding of how probability powers Machine Learning models, from data predictions to uncertainty handling.

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