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:
- Solving XOR problem using DNN
- Character recognition using CNN
- Face recognition using CNN
- Language modeling using RNN
- Sentiment analysis using LSTM
- Parts of speech tagging using Sequence to Sequence architecture
- Machine Translation using Encoder-Decoder model
- Image augmentation using GANs
- Mini-project on real world applications
Course Outcomes:
After the completion of this course, students will be able to:
- Apply deep neural network for simple problems (K3)
- Apply Convolution Neural Network for image processing (K3)
- Apply Recurrent Neural Network and its variants for text analysis (K3)
- Apply generative models for data augmentation (K3)
- 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.