OVERVIEW
Together with Red Dragon AI, SGInnovate is pleased to present the Deep
Learning Developer Series. The Jumpstart workshop is the first module
of the Deep Learning Developer Series and it is a prerequisite to the
advanced Deep Learning modules.
This two-day workshop is designed to introduce you the skills needed
to start your journey as a Deep Learning Developer. It goes through
the overall concepts and techniques for building a variety of Deep
Learning models for tabular data, image data, audio data and text
data.
At the end of the classroom training, 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 on
your project. This is especially useful for understanding how to apply
these skills for your unique applications.
By the end of the workshop, you will be able to take your new-found
Deep Learning knowledge and apply it to your job or projects straight
away!
This 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 modular customisation according to your
own pace and preference.
The curriculum will 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 identify the best techniques to
tackle various data science problems at hand.
THIS WORKSHOP IS ELIGIBLE FOR FUNDING SUPPORT. FOR MORE DETAILS,
PLEASE REFER TO THE "PRICING" TAB ABOVE.
IN THIS COURSE, PARTICIPANTS WILL LEARN:
* 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
* To build and use TensorFlow native estimators
* To build various types of Deep Learning models
* To build models for Computer Vision challenges
* To build 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
AGENDA
DAY 1 (13 NOVEMBER 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 math behind networks works_
* What is Deep Learning and examples of Deep Learning in Industry
* Math of Neural Networks and Back Propagation
* Activation functions
* Loss functions
* Optimisation 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
* VGG16
* 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 work on
* Q&A on projects
* Homework: What to bring for the next session
5:15PM – 5:30PM: Closing comments and questions
DAY 2 (14 NOVEMBER 2019)
8:45AM – 9:00AM: Registration
9:00AM – 10:45AM: 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)
* Using RNNs on character models
* Classifying Text
* Project questions and general follow up
10:45AM – 11:00AM: Tea Break
11:00AM – 12:30PM: Project Clinic 1
_Project questions and general follow up_
12:30PM – 1:30PM: Lunch
1:30PM – 2:30PM: Deep LEARNING FOR COMPUTER VISION
_Frameworks: TensorFlow, Keras, Estimators - Various types of Computer
vision tasks_
* Understanding more advance image networks
* Generative modelling for images
* Examples of Style Transfer and Deep Dream
2:30PM – 3:15PM: Building a Model for Structured Data with
TensorFlow estimators
_Frameworks: TensorFlow, Estimators, Datasets API - Understanding the
Estimator framework and its advantages_
* How does TensorFlow fit the APIs together into an end to end
system
* Building input pipelines
* Building a network for Structured Data
* Using tf.Data for pipelines
* Intro to the TensorFlow Datasets API
3:15PM – 3:30PM: Tea Break
3:30PM – 4:30PM: Project Clinic 2
_Project questions and general follow up_
4:30PM – 5:00PM: 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
[https://www.imda.gov.sg/industry-development/programmes-and-grants/individuals/critical-infocomm-technology-resource-programme-citrep]
CLAIM CONDITIONS:
* Meet the minimum attendance (75%)
* Complete and pass all assessments and / or projects
GUIDE FOR CITREP+ FUNDING ELIGIBILITY AND SELF-APPLICATION PROCESS:
* Individuals (Self-Sponsored)
[https://cdn2.hubspot.net/hubfs/3032335/Talent_Workshop-PDF/For_External_Use_CITREP_Funding_Briefing_Slides_self-sponsored_updated_190423.pdf]
* Organisation-Sponsored
[https://cdn2.hubspot.net/hubfs/3032335/Talent_Workshop-PDF/For_External_Use_CITREP_Funding_Briefing_Slides_org-sponsored_updated_190423.pdf]
* Students / NSF
[https://cdn2.hubspot.net/hubfs/3032335/Talent_Workshop-PDF/For_External_Use_CITREP_Funding_Briefing_Slides_students_updated_190423.pdf]
For more information on CITREP+ eligibility criteria and application
procedure, please click here
[https://www.imda.gov.sg/industry-development/programmes-and-grants/individuals/critical-infocomm-technology-resource-programme-citrep].
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.
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15/11/2019 Last update