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Applied Deep Learning Workshop

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Applied Deep Learning Workshop


Course Contents:

Day – 1: Introduction to Deep Learning & Neural Networks

  • Setting Up Environment for Deep Learning: Keras, Tensorflow, Jupyter etc
  • TensorFlow basics and Keras Basics
  • Theoretical Foundations of Deep Learning, Deep Learning vs Machine Learning (>> Just quick revision)
  • Deep Learning history, biological inspirations and demo with MNIST dataset (handwriting digit recognition) to start with.
  • Understanding Neural Network, How neural networks learn, Architecture of Neural Networks (>> Just quick revision)
  • Activations Functions: Sigmoid, Tanh, Softmax, Softmax crossentropy, Sigmoid Crossentropy (>> Just quick revision with formulae and derivatives)
  • Designing & Optimizing Neural Network Model
  • Building Deep Models and Hyperparameter Tuning
  • Basic ANN Types: Dense Neural Networks, Convolution Neural Networks, Recurrent Neural Networks

Day – 2: CNN Theory and Project

  • CNN: Deep-dive, Overfitting, Decaying Leaning, Dropout
  • CNN Project - finding the presence of a certain class of object in images, or something similar
  • Object Detection Systems/Computer Vision: YOLO (You Look Only Once) 
  • Deep Learning Hacks
  • System/project level tricks and regularization strategies

Day – 3: RNN Theory & Projects

  • Recurrent Neural Networks: LSTM, GRU CELL
  • Modern RNN Architectures/ Frameworks: Embed-Encode-Attend-Predict Framework - Developed by Google
  • RNN Projects

Day – 3: Time series modelling

  • One Example from Time series modelling using LSTM and one example application of NLP (with basics of NLP).
  • One example of Transfer Learning

Hands-on Projects:

  1. House Price Prediction using Neural networks ANN
  2. Classifying Emergency and non-emergency using CNN
  3. Multiclass Classification using CNN
  4. Pre Trained Models using CNN
  5. Time series and sequence Generations using RNN
  6. Text Extraction from Image using Advanced deep learning.
  7. Identifying the emotions from Image
  8. Chatbot using rule-based learning and RNN
  9. Sentiment Analysis
  10. Text-classification 

INSTRUCTORS: PRASHANT SAHU, Kamakshigari Suresh

Note: This boot camp will NOT discuss anything about the AutoEncoders and GANs, due to time constraints.

  • FEE: Rs. 2999/- for participants from Academics (full-time students, faculties). Rs. 4,999/- for ALL others.
  • Participation Certificate to be provided.
  • Attend ONLINE (as Zoom Meeting) or OFFLINE (at the venue)
  • Lecture recordings will be available for later viewing

 

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REGISTRATION LINK being updated. please visit after some time.

For enquiries contact: 8169543099 or dHJhaW5pbmcgfCB0ZWNoc21hcnRzeXMgISBjb20=



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