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
- House Price Prediction using Neural networks ANN
- Classifying Emergency and non-emergency using CNN
- Multiclass Classification using CNN
- Pre Trained Models using CNN
- Time series and sequence Generations using RNN
- Text Extraction from Image using Advanced deep learning.
- Identifying the emotions from Image
- Chatbot using rule-based learning and RNN
- Sentiment Analysis
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
REGISTRATION LINK being updated. please visit after some time.
For enquiries contact: 8169543099 or dHJhaW5pbmcgfCB0ZWNoc21hcnRzeXMgISBjb20=