[05x04] Naive Bayes Classifier | Classification | Supervised Learning | Machine Learning [Julia]

In this coding tutorial, you'll learn how to make Supervised Machine Learning Classification predictions by creating a Naive Bayes classifier from scratch using Julia. You'll also learn about the pros and cons of using this Classification approach compared to Logistic Regression.

- This tutorial is intended for students, hobbyists and amateurs.
- This tutorial is episode 04 of a 13-part series and is part of the Julia Machine Learning for Beginners playlist.
- Schedule: New tutorials are posted on Sundays / Mondays.
- Prerequisites: Julia, VS Code and Episode 503.

00:00 Intro
02:40 Data Set
04:42 Data Wrangling
14:05 Naive Bayes Classifier
28:33 Recap
32:06 Outro

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# Links for this tutorial
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# Data for this tutorial
https://raw.githubusercontent.com/julia4ta/tutorials/master/Series%2005/Files/tennis.csv

# Code for this tutorial
https://github.com/julia4ta/tutorials/tree/master/Series%2005/Tutorial%2005x04

# Link to Episode 503: Logistic Regression | Classification | Supervised Learning | Machine Learning
https://youtu.be/fiB7vjlcx0w

# Link to Krish Naik YouTube video [Tutorial 48- Naive Bayes' Classifier Indepth Intuition- Machine Learning]:
https://youtu.be/jS1CKhALUBQ

# Link to yogesh murumkar YouTube video [Naive Bayes Theorem explained with simple example (easy trick)]:
https://youtu.be/hPQiUk66bLM

# Link to tennis.csv at www.kaggle.com:
https://www.kaggle.com/pranavpandey2511/tennis-weather

# # # # # # # # # # # # # # # # # # # #
# Links for this series
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# Link to Series 5 Playlist [Julia Machine Learning for Beginners]
https://www.youtube.com/watch?v=jA6IYSCpIug&list=PLhQ2JMBcfAsi76O13sJzk4LXA_mu5sd9E

# Andrew Ng's Stanford Machine Learning Course
# Stanford CS229: Machine Learning | Autumn 2018
https://www.youtube.com/watch?v=jGwO_UgTS7I&list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU

# The Julia Programming Language
https://julialang.org/
https://docs.julialang.org/en/v1/
https://www.youtube.com/c/TheJuliaLanguage

# VS Code
https://code.visualstudio.com/

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Notice of Non-Affiliation and Disclaimer:
I am not affiliated, associated, authorized, endorsed by, or in any way officially connected with Andrew Ng or Stanford University.
Nor am I affiliated, associated, authorized, endorsed by, or in any way officially connected with The Julia Programming Language, Julia Academy, Julia Computing, Microsoft, or any of their subsidiaries or their affiliates.
Nor am I affiliated, associated, authorized, endorsed by, or in any way officially connected with any software, packages or libraries used in this video.
All marks, emblems and images are registered trademarks of their respective owners. Use of them does not imply any affiliation with or endorsement by them.

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