Workshop: Deep Learning Using Keras

Nov 16, 2019

09:30

Hotel Royal Orchid, Bengaluru

Do you want to jump into the Deep Learning? Are you still stuck on grasping how backpropagation works? Then this workshop is for you! The goal of this workshop is to get you up to speed with the advancements in Deep Learning with a practical perspective.   Along with this, you will also get to know about keras, a tool which has been getting heavy attention from the community as it provide simple higher level interface to build Deep Learning models. In this workshop, our objective is to make you comfortable to build image and text classification deep learning models using keras. And, you will also learn the building blocks of deep learning: MLP (Multi Layer Perceptron), CNN(Convolutional Neural Network) and RNN (Recurrent Neural Network).

Structure of the workshop

This is an 8-hour workshop and includes the following modules:
  • Introduction to Deep Learning
  • Getting started with Keras
  • Working with Image dataset
  • Understanding Building Block of a Neural Network
  • Building a simple neural network using Keras
  • Parameter tuning in Deep Learning
  • Solving an image classification challenge – Fashion MNIST
  • Image Processing using Convolutional Neural Network
  • Natural Language Processing using Recurrent Neural Network and LSTM
  • Solving a text classification challenge using RNN/ LSTM
  • Where to go from here?
Duration: 8 hours Note: Participants needs to carry their laptop for the workshop.

Prerequisites:

  • Python programming experience
  • Basic knowledge of Machine Learning
  • System Setup
    • Laptop with at least 4 GB of RAM
    • We will be using Google Colab for the workshop, hence make sure you have a google login and space on your google drive
    • Laptop running Linux/OSX/Windows
  •  Pre-Reads
Venue :- Hotel Royal Orchid, Bengaluru 1, Golf Avenue, Adjoining KGA Golf Course, HAL Old Airport Rd, Domlur, Bengaluru, Karnataka
Map :- goo.gl/maps/DwzYC72L8hT2
  • Xander Steenbrugge

    Head of Applied ML Research

    ML6

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