Course description
What will i learn?
Requirements
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1.1 Introduction to SVM
00:16:17
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1.2 How it Works SVM Concept Kernel Trick
00:11:17
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1.3 How it Works SVM Concept Kernel Trick
00:12:17
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1.4 Modeling and Evaluation of SVM in Python Part-01
00:13:44
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1.5 Modeling and Evaluation of SVM in Python Part-02
00:11:48
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1.6 Modeling and Evaluation of SVM in Python Part-03
00:14:31
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1.7 Modeling and Evaluation of SVM in Python Part-04
00:08:29
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1.8 Modeling and Evaluation of SVM in Python Part-05
00:07:47
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Quiz
0:00:00
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2.1 Introduction to Naive Bayes
00:06:02
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2.2 How it Works Bayes Theorem
00:09:50
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2.3 Naive Bayes for Text Classification
00:04:06
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2.4 Modeling and Evaluation of Naive Bayes in Python Part-01
00:07:54
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2.5 Modeling and Evaluation of Naive Bayes in Python Part-02
00:10:56
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2.6 Modeling and Evaluation of Naive Bayes in Python Part-03
00:07:06
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2.7 Modeling and Evaluation of Naive Bayes in Python Part-04
00:04:44
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Quiz
0:00:00
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3.1 Introduction to Decision Tree
00:11:14
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3.2 How Splitting Works in a Tree
00:10:48
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3.3 Advantages of Decision Tree
00:04:59
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3.4 Implementation in Python Part-01
00:11:41
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3.5 Implementation in Python Part-02
00:15:34
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3.6 Implementation in Python Part-03
00:03:15
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3.7 Implementation in Python Part-04
00:10:31
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3.8 Implementation in Python Part-05
00:06:31
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Quiz
0:00:00
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6.1 Introduction to Boosting and Xgboost how it works Weak Learners Concept
00:08:38
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6.2 Modeling and Evaluation of Boosting in Python Part-01
00:11:18
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6.3 Modeling and Evaluation of Boosting in Python Part-02
00:10:01
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6.4 Modeling and Evaluation of Boosting in Python Part-03
00:10:22
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6.5 Modeling and Evaluation of Boosting in Python Part-04
00:07:52
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6.6 Modeling and Evaluation of Boosting in Python Part-05
00:10:12
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6.7 Modeling and Evaluation of Boosting in Python Part-06
00:08:55
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Quiz
0:00:00
Ashok Veda
₹37900
₹60000
Lectures
38
Quizzes
7
Skill level
Beginner
Expiry period
Lifetime
