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Deep Learning Jumpstart Workshop (19, 21 and 23 October 2019)

SGInnovate and Red Dragon AI

Saturday, October 19, 2019 at 9:00 AM - Wednesday, October 23, 2019 at 10:00 PM (Singapore Standard Time Singapore Time)

Deep Learning Jumpstart Workshop (19, 21 and 23...

Ticket Information

Ticket Type Sales End Price Fee Quantity
Early Bird Module 1 (Ticket Inclusive of G.S.T)   more info 23h 1m $813.20 $0.00

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Event Details

Overview

 

Together with Red Dragon AI, SGInnovate is pleased to present the Deep Learning Jumpstart Workshop.

 

The Deep Learning Jumpstart Workshop is the first module of the Deep Learning Developer Series and is a prerequisite to the advanced Deep Learning modules. It goes through the overall concepts and techniques for not only understanding but building a variety of Deep Learning models for tabular data, image data, audio data and text data.

 

The curriculum will also cover many of the fundamentals needed in Deep Learning projects, as well as models such as Fully Connected Neural Networks, Convolutional Neural Networks and Recurrent Neural Networks. Real-world examples will be used to illustrate the best techniques to tackle various Data Science problems.

 

This workshop will be conducted on one full Saturday (19 October), followed by two weeknights (21 and 23 October) - specially designed for busy working professionals and students.

 

At the end of the workshop, once you understand the basics, you will work on your models and projects. Additional learning materials and assessments will be available online, with one-on-one sessions for you to ask questions about your project.

 

This workshop is eligible for funding support. For more details, please refer to the "Pricing" tab above.

 

In this course, participants will learn about:

  • The basic concepts of Neural Networks and an introduction to the mathematics of Deep Learning
  • An introduction to the Keras API and how it works as a higher level of abstraction for TensorFlow
  • Building and using TensorFlow native estimators
  • Building various types of Deep Learning models
  • Building models for Computer Vision challenges
  • Building models for Natural Language challenges

Prerequisites:

  • An interest in Deep Learning
  • Ability to read and follow code - We will send out some videos to help you with Python syntax specifically before the course begins

Pre-Workshop Instructions:

  • You MUST bring your laptop to this workshop
  • Please watch the introductory videos that will be sent out separately
  • Please experiment with the pre-exercises given

Deep Learning Developer Series

 

The Deep Learning Developer Series is a hands-on series targeted at developers and Data Scientists who are looking to build Artificial Intelligence (AI) applications for real-world usage. It is an expanded curriculum that breaks away from the regular eight-week full-time course structure and allows customisation according to your own pace and preference.

 

Agenda

 

Day 1 (19 October 2019)

 

08:45am – 09:00am: Registration
09:00am – 10:45am: Key Concepts behind Deep Learning and Introduction to the basic math
A simple introduction to how the math behind networks works

  • The math of Neural Networks and Back Propagation
  • Activation functions
  • Loss functions
  • Optimization functions

10:45am – 11:00am: Tea Break
11:00am – 12:30pm: Building your first Neural Network
Frameworks: TensorFlow, Keras - A look into the Keras API

  • Parts of a Model
  • Hidden Layers in action
  • Keras Layers API
  • Multi-Layer Perceptrons 
  • Setting Hyperparameters

12:30pm – 1:30pm: Lunch
1:30pm – 3:00pm: Building a Convolutional Neural Network (CNN)
Frameworks: TensorFlow, Keras - Convolutional Model Architectures

  • Convolution layers
  • Pooling layers
  • Dropout and how it affects networks
  • Combining Convolution layers

3:00pm – 3:15pm: Tea Break
3:15pm – 4:45pm: Using Transfer Learning for new problems
Frameworks: TensorFlow, Keras - Understanding the TensorFlow ecosystem and its advantages

  • Inception Network
  • Building a classifier with a pre-trained network
  • Reusing and retraining weights for a specific task

4:45pm – 5:15pm: Doing a Project
Frameworks: TensorFlow, Keras - Actually doing something is very important

  • Ideas for projects to do
  • Q&A on ‘doable projects’
  • Homework: What to bring to the next session

5:15pm – 5:30pm: Closing Comments and Questions

 

Day 2 (21 October 2019)

 

Evening Follow-Up Session 1
6:45pm – 7:00pm: Registration
7:00pm – 9:00pm: Deep Learning for Natural Language Processing
Frameworks: TensorFlow, Keras, Estimators - Using Deep Learning for problems related to language 

  • Ways to represent words and language
  • Intro to Recurrent Neural Networks (RNNs)
  • Classifying Text

9:00pm – 9:30pm: Project Clinic 1
Project questions and general follow up

 

9:30pm – 9:45pm: Closing Comments and Questions

 

Day 3 (23 October 2019)

 

Evening Follow-Up Session 2
6:45pm – 7:00pm: Registration
7:00pm – 9:00pm: Deep Learning for Computer Vision
Frameworks: TensorFlow, Keras, Estimators - Various types of Computer Vision tasks 

  • Understanding more advanced image networks
  • Generative modelling for images
  • Examples of Style Transfer and Deep Dream

8:00pm – 9:00pm: Building a Model for Structured Data with TensorFlow estimators
Frameworks: TensorFlow, Estimators, Datasets API - Understanding the Estimator framework and its advantages

  • What makes up an estimator
  • Canned estimator
  • Building a network for structured data
  • Estimator input function
  • Intro to the TensorFlow datasets API

9:00pm – 9:30pm: Project Clinic 2
Project questions and general follow up

9:30pm – 9:45pm: Closing Comments and Questions

You will be given two weeks to complete your online learning and individual project. 

Online Learning (9.5 hours)

  • Python Basics
  • Colabs and Notebooks
  • Neural Network Basics
  • Keras Basics
  • CNNs
  • RNNs
  • TensorFlow Estimators
  • Preprocessing Patterns
  • Project Walkthroughs
  • Cloud Training

Assessments:
You must fulfil the criteria stated below to pass and complete the course.

1.    Online Tests: Participants are required to score an average grade of more than 75% correct answers to the online questions.

2.    Project: Participants are required to present a project that demonstrates the following:

  • The ability to use or create a data processing pipeline that gets data in the correct format for running in a Deep Learning model
  • The ability to create a model from scratch or use transfer learning to create a Deep Learning model
  • The ability to train that model and get results
  • The ability to evaluate the model on held out data

 

Pricing

 

Funding Support

 

This workshop is eligible for CITREP+ funding.

 

CITREP+ is a programme under the TechSkills Accelerator (TeSA) – an initiative of SkillsFuture, driven by Infocomm Media Development Authority (IMDA).

 


*Please see the section below on ‘Guide for CITREP+ funding eligibility and self-application process’

 

Funding Amount: 

  • CITREP+ covers up to 90% of your nett payable course fee depending on eligibility for professionals

Please note: funding is capped at $3,000 per course application

  • CITREP+ covers up to 100% funding of your nett payable course fee for eligible students / full-time National Servicemen (NSF)

Please note: funding is capped at $2,500 per course application

Funding Eligibility: 

  • Singaporean / PR
  • Meets course admission criteria
  • Sponsoring organisation must be registered or incorporated in Singapore (only for individuals sponsored by organisations)

Please note: 

  • Employees of local government agencies and Institutes of Higher Learning (IHLs) will qualify for CITREP+ under the self-sponsored category
  • Sponsoring SMEs organisation who wish to apply for up to 90% funding support for course must meet SME status as defined here

Claim Conditions: 

  • Meet the minimum attendance (75%)
  • Complete and pass all assessments and / or projects

Guide for CITREP+ funding eligibility and self-application process:

For more information on CITREP+ eligibility criteria and application procedure, please click here

 

In partnership with:

   Driven by:

 

For enquiries, please send an email to learning@sginnovate.com

 

Trainer

 

 

Dr Martin Andrews
Martin has over 20 years’ experience in Machine Learning and has used it to solve problems in financial modelling and has created AI automation for companies. His current area of focus and speciality is in natural language processing and understanding. In 2017, Google appointed Martin as one of the first 12 Google Developer Experts for Machine Learning. Martin is also one of the co-founders of Red Dragon AI. 

 

 

Sam Witteveen
Sam has used Machine Learning and Deep Learning in building multiple tech start-ups, including a children’s educational app provider which has over 4 million users worldwide. His current focus is AI for conversational agents to allowa humans to interact easier and faster with computers. In 2017, Google appointed Sam as one of the first 12 Google Developer Experts for Machine Learning in the world. Sam is also one of the co-founders of Red Dragon AI. 

Have questions about Deep Learning Jumpstart Workshop (19, 21 and 23 October 2019)? Contact SGInnovate and Red Dragon AI

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When & Where


BASH, Level 3
79 Ayer Rajah Crescent, via Lift Lobby 3
139955
Singapore

Saturday, October 19, 2019 at 9:00 AM - Wednesday, October 23, 2019 at 10:00 PM (Singapore Standard Time Singapore Time)


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