B.E. (Biomedical Engineering) Machine Learning Laboratory Abbreviated As ML Lab Syllabus - Mumbai University 2026
This is the Fourth Year Biomedical Rev 2019 C Scheme syllabus under REV-2019 'C' Scheme, in force from the academic year 2022-23. The University has not yet published an NEP 2020 syllabus above Semester IV for this branch, and this is the scheme its examinations are set on.
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Syllabus for Machine Learning Laboratory (Abbreviated as ML Lab)
Objectives
- To develop competency in logical thinking, computer programming and knowledge application.
- To train and motivate for higher education and research in order to make contribution to state of the art health care for all Course Learner will be able to…
Outcomes
- Understand the fundamental techniques and applications in neural networks, deep learning and machine learning
- Understand supervised and unsupervised learning, back propagation and gradient descent algorithms
- Understand and implement efficient computational techniques using neural networks, deep learning and machine learning
- Design and implementation of neural network models with deep learning and machine learning will be strong base for designing artificial intelligent systems University of Mumbai, Biomedical Engineering, Rev 2022-23 57 Syllabus: Same as that of (BMC702) Machine Learning (ML) List of Experiments: (Any Seven)
- 1 Implement the activation functions used in the neural network
- 2 Implement ANDNOT and XOR function using McCulloch-Pitts neural net
- 3 Implementation of learning rules for neural network
- 4 Implementation of backpropagation with gradient descent algorithm neural network
- 5 Design and implement the neural network model for estimation problem.
- 6 Design and implement the neural network model for classification problem
- 7 Optimize the neural network model for estimation problem.
- 8 Optimize the neural network model for classification problem.
- 9 Design and implement the neural network model for estimation problem with deep learning
- 10 Design and implement the neural network model for estimation problem with deep learning Any other experiment based on syllabus which will help learner to understand topic/concept. Assessment: Term Work: Term work shall consist of minimum 7 experiments. The distribution of marks for term work shall be as follows: Laboratory work (Experiments): 10 Marks Laboratory work (Journal) : 10 Marks Attendance : 05 Marks The final certification and acceptance of term work ensures the satisfactory performance of laboratory work and minimum passing in the term work.
Text books
- 1 Introduction to Machine Learning, 3rd edition, Ethem Alpaydin, PHI Learning Private Limited, New Delhi, 2015
- 2 Deep Learning by Josh Patterson and Adam Gibson, O’Reilly Media, Inc., Gravenstein Highway North, Sebastopol CA, 2017
- 3 Neural Networks and Learning Machines Third Edition, Simon Haykin, Pearson, Prentice Hall, 2009
- 1 Machine learning in Action, Peter Harrington, dreamtech Press, New Delhi, 2012
- 2 Machine learning, Tom M, Mitchell, Mc Graw Hill Education(India) Private Limited New Delhi, 2013 Practical examination will be based on experiments and related topics in the laboratory sessions. University of Mumbai, Biomedical Engineering, Rev 2022-23 58
Reproduced from the University of Mumbai syllabus for B.E. (Biomedical Engineering) under REV-2019 'C' Scheme, in force from the academic year 2022-23. Wording is as printed in that syllabus. The University sets no module list for this course; what she publishes is the objectives, outcomes and assessment guidelines reproduced above.
The complete syllabus
This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.