Machine Learning detail syllabus for Textile Technology (Textile Technology), 2021-22 scheme is taken from AKTUs official website and presented for the AKTU B.Tech students. For the course code (KOE073), exam duration, teaching hr/week, practical hr/week, total marks, internal marks, theory marks, duration, credits, and other details do visit complete semester subjects post given below.
For the Textile Technology 7th Sem Syllabus for AKTU B.Tech 2021-22 Scheme you can visit Textile Technology 7th Sem 2021-22 Scheme. For the Open Elective-2 scheme of Textile Technology 7th Sem 2021-22 regulation do refer to Open Elective-2 Textile Technology 7th Sem scheme. The detail syllabus for machine learning is as follows.
Unit I
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Unit II
DECISION TREE LEARNING – Decision tree learning algorithm-Inductive bias- Issues in Decision tree learning; ARTIFICIAL NEURAL NETWORKS – Perceptrons, Gradient descent and the Delta rule, Adaline, Multilayer networks, Derivation of backpropagation rule Backpropagation AlgorithmConvergence, Generalization.
Unit III
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Unit IV
Computational Learning Theory: Sample Complexity for Finite Hypothesis spaces, Sample Complexity for Infinite Hypothesis spaces, The Mistake Bound Model of Learning; INSTANCE-BASED LEARNING – k-Nearest Neighbour Learning, Locally Weighted Regression, Radial basis function networks, Case-based learning.
Unit V
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Text Books:
- Tom M. Mitchell,’Machine Learning, McGraw-Hill Education (India) Private Limited, 2013.
- Ethem Alpaydin,’Introduction to Machine Learning (Adaptive Computation and Machine Learning), The MIT Press 2004.
- Stephen Marsland, ‘Machine Learning: An Algorithmic Perspective, CRC Press, 2009.
- Bishop, C., Pattern Recognition and Machine Learning. Berlin: Springer- Verlag.
For the syllabus of all the subjects of B.Tech Textile Technology 7th Sem, 2021-22 scheme do visit Textile Technology 7th Sem syllabus subjects.
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.