Machine Learning for Applications in Language, Vision and Control @ National Institute of Technology Andhra Pradesh


Participants Information

Participants: 40
Speakers:06
Female participants:18
Male participants:22
Participants from SC/ST category:04
Research Scholars:02

Lab Sessions

  • ML Frameworks

Topics Covered

  • Introduction to Machine Learning
  • Supervised/ Unsupervised/ Semi Supervised Learning
  • R for ML
  • Unsupervised learning on High Dimensional Data
  • Latent Factor Models
  • Case Studies on ML for Computer Vision
  • Deep RL
  • Sequence Labeling Models
  • Applications of conditional Random Fields
  • LSTM
  • Attention Based Models
  • GoogleNet, Resnet, U-Net
  • Fast RCNN, GAN
  • Case Studies: Image Classification, Semantic Segmentation, Object Localization, Super Resolution
  • Visual Attention Models for ML
  • Case Studies: ML for Biometrics
  • Large Scale Learning Algorithms

Highlights

List of Speakers

Dr. S. Karthick Assistant Professor, NIT AP


Dr. K. Hima Bindu, Assistant Professor, NIT AP


Dr. S. Nagesh Bhattu, Assistant Professor, NIT AP


Dr. P. Balamurugan, Assistant Professor, IIT Bombay


Dr. Rajarshi Pal, Assistant Professor, IDRBT, Hyderabad


Dr. K. Phani Krishna, Assistant Professor, NIT AP



Feedback Summary

  • FDP was very useful to the participants who are aspiring for Ph.D.

  • Planning and course preparation was good.

  • Lab Sessions were very effective.

  • Suggestions from Participants

  • More hands on sessions are required.