Artificial Intelligence and Deep Learning for Instrumentation
Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.
English Book & Chapters
English Book Coming Soon
We are working hard to add this material. Stay tuned for updates!
Follow on Instagram for UpdatesGTU Previous Year Papers
Papers Coming Soon
We are working hard to add this material. Stay tuned for updates!
Follow on Instagram for UpdatesArtificial Intelligence and Deep Learning for Instrumentation Syllabus — Unit-wise Content
The official GTU curriculum for Artificial Intelligence and Deep Learning for Instrumentation (subject code 3730309) as prescribed for IACI · Semester 3 divides the course into 7 units, covering 20 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3730309)Unit 1 Machine Learning
- Knowledge and Learning
- learning by Advise
- learning in problem Solving
- Symbol Based Learning
- Explanation Based Learning
- Version Space
- ID3 Decision Based Induction Algorithm
- Unsupervised Learning
- Reinforcement Learning
- Supervised Learning: Perceptron Learning
- Back propagation Learning
- Competitive Learning
Unit 2 Feed Forward Neural Networks, Back propagation, Gradient Descent
- Momentum Based GD, Nesterov Accelerated GD, Stochastic GD. 4 10
Unit 4 Auto encoders and relation to PCA, Regularization in auto encoders, De
- noising auto encoders
- Sparse auto encoders. 4 10
Unit 5 Regularization
- Bias Variance Tradeoff
- Early stopping
- Dataset augmentation. 4 10
Unit 8 Recurrent Neural Networks, Back propagation through time (BPTT),
- Vanishing and Exploding Gradients
- Truncated BPTT, GRU, LSTMs. 7 16
Study on Android App:
