ieee-dl-bootcamp

Resources for the Deep Learning Bootcamp organized by IEEE Bangalore Section

Schedule

Timings	Title	Description	Pre-requisites
09:00 to 09:30	Registration
09:30 to 10:15	Introduction to Deep Learning - Demystifying DL - Part 1	Introduction to ML, feature extraction, neural networks, backpropogation and autoencoders. (Slides)
10:15 to 11:00	Introduction to Deep Learning - Demystifying DL - Part 2	Convolutional Neural Networks, Recurrent Neural Networks, Sequence-to-Sequence models, Generative Models. (Slides)
11:00 to 11:15	Networking Tea Break
11:15 to 12:30	Hands-on session: Building a classifier from scratch	Use basic tensor operations from numpy to build a MLP to classify handwritten digits (Notebook)	Install Python 3, Keras and MXnet Open Python interepreter Run `from keras.datasets import mnist` Run `(x_train, y_train), (x_test, y_test) = mnist.load_data()` This will download the data needed for the session onto your computer
12:30 to 13:30	Lunch
13:30 to 15:30	Hands-on session: Designing deep learning models visually	Using Neural Network Modeller (NNM) available in Watson Studio (Slides)	Create Watson Studio accounts
15:30 to 16:00	Networking Tea Break
16:00 to 17:00	Latest trends and future directions	Brief discussion over current and future trends in deep learning and AI such as architecture search, testing and debugging AI models, model debiasing, and transfer learning (Slides)
17:00	Conclusion and Curtains down