NIT Warangal | WORKSHOP ‘KARYASHALA’ ON Deep Learning Methods for Real Time Applications, Apply by 30 July 2022
Overview:
HIGH-END WORKSHOP ‘KARYASHALA’ on Deep Learning Methods for Real-Time Applications (1st August – 7th August 2022) Funded by SCIENCE & ENGINEERING RESEARCH BOARD(SERB)-DST (GOI) Organised by the Department of Computer Science and Engineering, NIT Warangal, Warangal.
Topic:
- Introduction to Machine Learning and Deep Learning
- Research in Machine Learning and Deep Learning
- Introduction to Python, Python Flow Control, Python Functions, Python Files, Python Objects& Classes, Pandas, Numpy, Matplotlib
- Supervised Learning Methods, Neural Networks
- Back Propagation Algorithm, CNN, Different Models,
- Transfer Learning and Data Augmentation
- Python Iterator, Python Generator, Python Closure, Python Decorators, PythonProperty
- TensorFlow, Keras Google Colab
- Hands-on session on NN and CNN Models
- Medical Image analysis applications
- Objection Detection: RCNN, FRCNN models
- Image Segmentation: FCN, Unet and ResUnet Models
- Hands-on session on RCNN, Unit, AND YOLO models with Real-time applications
- GANS and Types of GANS with Applications
- Sequence Models: RNN, LSTM, Bi-LSTM
- Attention Layers and Transformers
- Hands-on session on RNN, LSTM, and BERT models
Eligibility:
Who Can Apply The scheme is meant to support regular PG level students and early stage Ph.D. level Students from universities, colleges, private academic institutions, and newly established institutes in handling/troubleshooting high-end scientific instruments and such skill development on themes required for research work.
Selection Criteria:
There is no registration fee for the participants of this workshop. The maximum number of students limit is 25. The list of selected participants will be intimated through e-mail.
All the selected participants will be provided FREE boarding & lodging in the institute guest house. And TA (sleeper class) will be paid for the selected participants.
Important Dates:
- Last date (Application & DD) 30.7.2022
- Selection List Email 31.7.2022
- Duration 1.8.2022 to 7.8.2022