32 -Dimensionality Reduction | AIML | Principal Component Analysis | Linear Discriminant Analysis
1:59 Curse of Dimensionality Reduction
5:11 Feature Extraction v/s Feature Selection
10:37 Subset Selection - Forward and Backward Selection
17:18 Principle component analysis
20:40 Understand PCA with Example
38:28 Linear Discriminant Analysis
Module7:
Dimensionality Reduction:
Introduction,
Subset Selection,
Principal Components Analysis,
Multidimensional Scaling,
Linear Discriminant Analysis.
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Please refer to the previous video for better comprehension.
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Lecture 1: Introduction of AI - • 1-Introduction to Artificial Intellig...
Lecture 2: Introduction of AI - • 2-Introduction to Artificial Intellig...
Lecture 3: Introduction of AI - • 3-Introduction to Artificial Intellig...
Lecture 4: Introduction of AI - • 4-Introduction to Artificial Intellig...
Lecture 5: Introduction of AI - • 5-Introduction to Artificial Intellig...
Lecture 6: Introduction of AI - • 6-Introduction to Artificial Intellig...
Lecture 7: Search Strategies - • 7 - Search Strategies | AIML | Probl...
Lecture 8: Search Strategies - • 8 - Search Strategies | AIML | Type...
Lecture 9: Search Strategies - • 9 - Search Strategies | AIML | Heuri...
Lecture 10: Search Strategies - • 10 - Search Strategies | AIML | A* A...
Lecture 11: Search Strategies - • 11 - Search Strategies | AIML | Alph...
Lecture 12: Search Strategies - • 12 - Search Strategies | AIML | AO* ...
Lecture 13: Search Strategies - • 13 - Search Strategies | AIML | Cons...
Lecture 14: Artificial Neural network - • 14 - Artificial Neural Network | AIM...
Lecture 15: Artificial Neural network - • 15 - Artificial Neural Network | AIM...
Lecture 16: Artificial Neural network - • 16 - Artificial Neural Network | AIM...
Lecture 17: Artificial Neural network - • 17 - Artificial Neural Network | AIM...
Lecture 18: Artificial Neural network - • 18 - Artificial Neural Network | AIM...
Lecture 19: Artificial Neural network - • 19 - Artificial Neural Network | AIM...
Lecture 20: Introduction to ML - • 20 - Introduction to Machine Learning...
Lecture 21: Introduction to ML - • 21 - Introduction to Machine Learning...
Lecture 22: Introduction to ML - • 22 - Introduction to Machine Learning...
Lecture 23: Forecasting and Learning Theory - • 23 - Forecasting and Learning Theory...
Lecture 24: Forecasting and Learning Theory - • 24 - Forecasting and Learning Theory...
Lecture 25: Forecasting and Learning Theory - • 25 - Forecasting and Learning Theory...
Lecture 26: Forecasting and Learning Theory - • 26 - Forecasting and Learning Theory...
Lecture 27: Forecasting and Learning Theory - • 27 - Forecasting and Learning Theory...
Lecture 28: Kernel Machines & Ensemble Methods - • 28 - Kernel Machines & Ensemble Metho...
Lecture 29: Kernel Machines & Ensemble Methods - • 29 - Kernel Machines & Ensemble Metho...
Lecture 30: Kernel Machines & Ensemble Methods - • 30 - Kernel Machines & Ensemble Metho...
Lecture 31: Kernel Machines & Ensemble Methods - • 31 - Kernel Machines & Ensemble Metho...
Lecture 32: Kernel Machines & Ensemble Methods - • 32 -Dimensionality Reduction | AIML |...