FREE
AKTU Deep Learning and Neural Network (MNAM601) Syllabus PDF – B.Tech Minor Degree in Artificial Intelligence and Machine Learning
Deep Learning and Neural Network MNAM601
All syllabus, notes, question bank & PYQ for this subject
Free
Download now
- English
- Semester 6
- 0 downloads
- 0 views
Official AKTU syllabus of Deep Learning and Neural Network (MNAM601) for B.Tech Minor Degree in Artificial Intelligence and Machine Learning – 4 credits, L-T-P 3-1-0. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Deep Learning and Neural Network
Download PDFMNAM601 · 4 credits · L-T-P 3-1-0
Course Outcomes
At the end of course , the student will be able to understand
| CO 1 | To strengthen important Mathematical concepts required for Deep learning and neural network. |
| CO 2 | To get a detailed insight of advanced algorithms of ML. |
| CO 3 | Produce Python code or simulate training algorithms ; |
| CO 4 | Critically evaluate and Creating and deploying networks ; |
Course Content
| Unit | Topic | Proposed Lecture |
|---|---|---|
| I | Information flow in a neural network, understanding basic structure and ANN. | 08 |
| II | Training a Neural network, how to determine hidden layers, recurrent neural network. | 08 |
| III | Convolutional neural networks, image classification and CNN. | 10 |
| IV | RNN and LSTMs. Applications of RNN in real world. | 09 |
| V | Creating and deploying networks using tensor flow and keras. | 7 |
Text Books
- John Paul Mueller, Luca Massaron, Deep Learning for Dummies, John Wiley & Sons.
- Adam Gibson, Josh Patterson, Deep Learning, A Practitioner’s Approach, Shroff Publisher /O’Reilly Publisher Media.
- Christopher M. Bishop, Neural Networks for Pattern Recognition, Oxford. Corresponding Online Resources:
- Fuzzy Logic and Neural Networks, https://swayam.gov.in/nd1_noc20_ge09/preview.
Ratings & Reviews
No reviews yet — share your experience with this item.