Quick Overview: Pattern Recognition by Prof. C.A. Murthy & Prof. Sukhendu Das,Department of Computer Science and Engineering,IIT Madras. Support Vector Machines (SVMs) are one of the most powerful tools in a Machine Learning — but they can also feel a little ... Pattern Recognition by Prof. P.S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore. For more ...

Mod 06 Lec 40 Support - Detailed Overview & Context

Pattern Recognition by Prof. C.A. Murthy & Prof. Sukhendu Das,Department of Computer Science and Engineering,IIT Madras. Support Vector Machines (SVMs) are one of the most powerful tools in a Machine Learning — but they can also feel a little ... Pattern Recognition by Prof. P.S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore. For more ... Digital System design with PLDs and FPGAs by Prof. Kuruvilla Varghese,Department of Electronics & Communication ... Operations and Supply Chain Management by Prof. G. Srinivasan , Department of Management Studies, IIT Madras. For more ... ICT Basics by Prof. T.V. Prabhakar,Department of Computer Science and Engineering, IIT Kanpur. For more details on NPTEL visit ...

Organizational Behaviour by prof. Dr. Susmita Mukhopadhyay, Department of Management, IIT Kharagpur. For more details on ... Advanced Geotechnical Engineering by Dr. B.V.S. Viswanadham,Department of Civil Engineering,IIT Bombay.For more details on ... Linux Programming & Scripting by Anand Iyer,Director, Calypto Design Systems.For more details on NPTEL visit

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Mod-06 Lec-40 Support Vector Machine (SVM)
Mod-06 Lec-42 Examples of Uses or Application of Pattern Recognition; And When to do clustering
Lec-40: Support Vector Machines (SVMs) | Machine Learning
Mod-06 Lec-37 Data Condensation, Feature Clustering, Data Visualization
Mod-09 Lec-34 Support Vector Regression and ?-insensitive Loss function, examples of SVM learning
Mod-06 Lec-41 FCM and Soft-Computing Techniques
Mod-06 Lec-43 Examples of Real-Life Dataset
Mod-06 Lec-41 Altera and Actel FPGAs
Mod-06 Lec-22 Integrated model, ROL for normal distribution of LTD and given mean
Mod-06 Lec-35 Comparison Between Performance of Classifiers
Mod-06 Lec-13 Linear Discriminant Functions; Perceptron -- Learning Algorithm and convergence proof
Mod-07 Lec-40 Highlights Week-6
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