AD3511: Deep Learning Laboratory syllabus for AI&DS 2021 regulation

Deep Learning Laboratory detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the AI&DS students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Artificial Intelligence & Data Science 5th Sem scheme and its subjects, do visit AI&DS 5th Sem 2021 regulation scheme. The detailed syllabus of deep learning laboratory is as follows.

Course Objectives:

• To understand the tools and techniques to implement deep neural networks
• To apply different deep learning architectures for solving problems
• To implement generative models for suitable applications
• To learn to build and validate different models

List of Experiments:

1. Solving XOR problem using DNN
2. Character recognition using CNN
3. Face recognition using CNN
4. Language modeling using RNN
5. Sentiment analysis using LSTM
6. Parts of speech tagging using Sequence to Sequence architecture
7. Machine Translation using Encoder-Decoder model
8. Image augmentation using GANs
9. Mini-project on real world applications

Course Outcomes:

After the completion of this course, students will be able to:

1. Apply deep neural network for simple problems (K3)
2. Apply Convolution Neural Network for image processing (K3)
3. Apply Recurrent Neural Network and its variants for text analysis (K3)
4. Apply generative models for data augmentation (K3)
5. Develop real-world solutions using suitable deep neural networks (K4)

For detailed syllabus of all other subjects of Artificial Intelligence & Data Science, 2021 regulation curriculum do visit AI&DS 5th Sem subject syllabuses for 2021 regulation.

For all Artificial Intelligence & Data Science results, visit Anna University AI&DS all semester results direct link.