Deep Learning & Applications (Parallel Architectures)

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Principal Coordinator :
  • Prof. Aparajita Ojha, IIITDM Jabalpur
  • Joint- Principal Coordinators
  • Dr. M P Singh, NIT Patna
  • Dr. S. Vipparthi MNIT Jaipur
  • Dr. Amey Karkare, IIT Kanpur,
  • Prof RBV Subramanyam NIT Warangal
  • Dr Raksha Sharma, IIT Roorkee

  • Course Fee Details:


    Academic (student/faculty): 500 INR
    Industry People/ Others : 1000 INR
    Foreign Participants: 4000 INR

    Payment Details:
    Bank Name: Allahabad Bank (Merge to Indian Bank)
    Account Name: NIT Patna
    Account No.: 50380476798
    IFSC Code: IDIB000B810


    Speakers:

    (i) Industry support from NVidia, MathWorks (MATLAB) (ii) Dr. Anupama Ray, IBM (iii) Dr. Ritu, Intel, (iv) Prof. R. Venkatesh Babu, IISc Banglore (v) Dr. Biplab Banerjee IITB Experts from host institutes- (iii) Prof. R. Balasubramanian, IITR (iv) Prof. Aparajita Ojha, IIITDMJ (v) Dr. Partha Pratim Roy, IITR (vi) Dr. Santosh K. Vipparthi, MNITJ


    Course contents:


    S.No. Topics
    1 Artificial Neural Networks (ANNs)- Introduction to Deep Learning and Motivation. Brief introduction of Artificial Neural Networks (ANN), Perceptrons, Multilayer perceptron (MLP), Back propagation training for MLP, Stochastic gradient descent. Applications to some practical classification problems.
    Hands on: Demonstration and implementation of Shallow and Deep architecture, introduction to Python, Tensorflow and Keras.
    2 Regularization, Hyperparameter Tuning and Autoencoders - Deep Feed forward Networks - Regularization - drop out, Minibatch gradient descent, RMSProp and Adam optimization, Autoencoders and Their Types Hands on: Hyper parameter tuning and regularization practice, Minibatch gradient descent, Autoencoders
    3 Convolutional Networks - The Convolution Operation, Pooling, Basic architecture of a Convolution Neural Network, Variants of the Basic Convolution Model, Evolution of Convolution NN Architectures - AlexNet, ResNet and other architectures. Hands on : Convolution neural network application using Tensorflow and Keras, Autoencoders using CNN, Building an application for classification and feature extraction.
    4 Sequence Modeling- Recurrent and Recursive Nets - Unfolding Computational Graphs, Recurrent Neural Networks, The Long Short-Term Memory and Other Gated RNNs. Hands on : Language modeling and machine translation, Chatbots.
    5 Generative Adversarial Networks, Object Detection Algorithms- GAN and their variants- R-CNN , YOLO and SSD Hands on– Object detection, Realistic Image Generation and face recognition

    Core Team Members, E&ICT Academy, NIT Patna:

    Dr. Bharat Gupta( CI E & ICT Academy,NIT Patna)
    Email: bharat@nitp.ac.in

    Dr. MP Singh ( CI E & ICT Academy,NIT Patna)
    Email: mps@nitp.ac.in

    Website: http://old.nitp.ac.in/ict/index.php



    Contact us :
    Electronics and ICT Academy
    National Institute of Technology, Patna
    AshokRajpath, Patna 800005
    Email: eictapatna@nitp.ac.in
    Website: http://old.nitp.ac.in/ict