Deep Learning @ Sree Vidyanikethan Engineering College, Tirupati

Participants Information

Participants:	55
Speakers:	05
Female participants:	14
Male participants:	41
Participants from SC/ST category:	04
Research Scholars:	01

Topics Covered

• Multi-Dimensional Neural Networks
• Linear filter Model of Synapses, Hopfield neural networks
• Hybrid Neural Networks, Linear Congruential sequences, Optimization of quadratic forms
• Brain information Technology: neuro Computing: Novel perspectives
• Sequence labeling
• Word Embeddings
• ISTM
• Artificial Neural Networks-Introduction
• Multilayered Perceptron
• Back Propagation in Neural Networks
• Convolutional Neural Networks
• Basics of Tensor Flow and Keras, Deep Learning with Tensor flow and Keras
• Deep Learning approach for Image classificatrion using Tensor flow
• Image Segmentation with Convolutional Neural Networks using Tensor flow(Deep Learning approach)
• Image classification analysis with Convolutional Neural Networks in Keras(Deep Learning approach)
• Introduction to CNN's, Different CNN model(Vgg net, alexnet, Resenet models)
• Medical data applications using Deep Learning
• Image and computer vision applications using Deep Learning
• Object detection and action recognisition
• NLP Introduction
• Why NLP for Indian Languages
• Word Representation for Deep Learning
• Recent Research Directions in NLP and Social Media Text

List of Speakers

Prof. Ramamurthy, Associate Professor, IIIT Hyderabad

Dr. M. Srinivas, Assistant Professor, IIIT Hyderabad

Dr. S. Nagesh Bhatt, Assistant Professor, NIT Andhra Pradesh

Dr. Ananda Kumar. M, Assistant Professor, NIT Surathkal

Dr. M. Srinivas, Assistant Professor, NIT Warangal

Feedback Summary

Good Infrastructure.

Organizing of FDP was Excellent, All sessions were good.

Text book given is useful for future reference.

Good Accomodation.

Suggestions from Participants

Required more hands on sessions.

Required more real time examples.

More Application oriented sessions are Required.

Python basics are required.