#80. Classification Algorithms Made Simple | Machine Learning Full Course | AI and ML Full Course

Описание: In this tutorial, we explore Classification Algorithms, a core part of Supervised Learning in Machine Learning.

You will learn how algorithms like Logistic Regression, K-Nearest Neighbors (KNN), Decision Trees, Random Forests, Naïve Bayes, Support Vector Machines (SVM), and Boosting techniques classify data into distinct categories.

We will also discuss binary vs. multi-class classification, model selection, and real-world applications in areas such as spam detection, disease diagnosis, and image recognition.

Perfect for both beginners and advanced learners, this session simplifies complex ML concepts into clear, practical insights.
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Github Link: https://github.com/edumentordeepti/Fo...
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Chapter/ Timestamp:
00:00 - Intro
00:24 - Types Classification Algorithm
04:40 - Types of Classfication Algorithms Used in ML
05:51 - Logistic Regression (Binary and Multi)
09:05 - Naive Bayes Classifier (Binary and Multi)
12:22 - K Nearest Neighbor (Binary and Multi)
19:51 - Support Vector Machine (Binary and Multi)
26:21 - Decision Tree (Binary and Multi)
34:42 - Decision Tree - Random Forest (Multi Class)
39:24 - Bagging
40:00 - Ada Boosting
45:16 - XG Boosting
47:07 - Outro
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DISCLAIMER:
This video is created for educational purposes only. We do not own any copyrights, all code, resources shared are for learning only and all rights go to their respective owners. Please respect licenses and terms of use when implementing in your projects. The usage is non-commercial and we do not make any profit from it. The sole purpose of this vides is to " Learn & Grow... " together in the field of Artificial Intelligence and Machine Learning.