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Advanced Computer Vision with TensorFlow Keras

TensorFlow has been gaining immense popularity among the mahcine learning and artificial intelligence community due to its power. Keras is a very popular high level Tensorflow API due to its simplicity to use. This course will help you leverage the power of TensorFlow and Kears to perform advanced image processing and object detection. 

You will implement multiple state-of-the-art computer vison algorith from scratch using the TensorFlow-Keras API. This course will teach you how to construct efficient CNN architectures with CNN Squeeze layers and delayed downsampling . The topics includes:

  • CNN
  • Transfer Learning
  • SqueezeNET
  • ResNET
  • R-CNN Based Object Detection
  • YOLO Based Object Detection


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Course Code: CRS-N-0045175

Course Booking

$498.00

Course Date

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Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.


Training Grant and Subsidy

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Course Details

Day 1

Module 1 Introduction to Tensorflow-Keras

  • Overview of Tensorflow Keras
  • Loss Function
  • Optimizer
  • Metrics

Module 2 Convolutional Neural Network (CNN)

  • What is CNN?
  • Tensorflow-Keras Layers for CNN
  • Tensorflow-Kearss Functional API
  • Image Processing and Augmentation

Module 3 Image Classsifcation with Transfer Learning

  • Overview VGG Network Architecture
  • VGG Implementation with Tensorflow-Keras
  • Cats and Dogs Dataset
  • Transfer Learning and Feature Extraction
  • Transfer Learning and Fine Tunning  

Module 4 Advanced CNN: SqueezeNet and ResNET

  • Overview of SqueezeNet Architecuture
  • SqueezeNet Implementation
  • Overview of ResNET Architecture
  • ResNET Implementation

 

Day 2

Module 7 R-CNN Based Object Detection 

  • Overview of R-CNN Object Detection
  • R-CNN Implementation
  • Fast R-CNN Implemenation
  • Faster R-CNN Implemenaton
  • Mask R-CNN Implementaiton

Module 8 Real Time Object Detection with YOLO

  • Overview of YOLO Architecuture 
  • YOLO Implemenation

Module 9 Image Creation with Conditoinal Adversial Generative Network 

  • Introduction to Adversial Generative Network (GAN)
  • What is Conditonal GAN
  • Image Generation with GAN

Who Should Attend

  • Data Scientists
  • Data Analysts
  • Machine Learning Engineers and Developers

Prerequisite

Participants need to be acquainted with the following knowledge before attending the class

  • Python
  • Tensorflow
  • Keras

Trainers

Chief Trainer in Tertiary CoursesDr. Alfred Ang is the founder of Tertiary Courses. He is a serial entrepreneur. He founded OSWeb2Design Singapore Pte Ltd in 2007 offering web development, e-commerce store development, graphics design, ebook publishing, mobile apps development, and digital marketing services. He established the first online gardening store in Singapore, Eco City Hydroponics Pte Ltd in 2000, offering a wide range of gardening products such as seeds, plant nutrients, hydroponics kits etc. Eco City Hydroponics has become the most popular and successful gardening store in Singapore. He founded Tertiary Infotech Pte Ltd in 2012 and transformed the business to a training platform, Tertiary Courses in 2014. Tertiary Courses offers a wide range of SkillsFuture courses for PMETs to upgrade their skills and knowledge. He also established Tertiary Courses Malaysia in 2016. He also founded Tertiary Robotics in 2015 offering Arduino, Raspberry Pi, Microbit and Robotics products

Dr. Alfred Ang earned his Ph.D. from National University of Singapore in 2000, majoring in Electrical and Electronics Engineering. He also completed an online MBA course with U21 Global based in Australia. He obtained his B.Sc (Hons) from National University of Singapore in 1992, majoring in Physics. He topped his Physics cohort for 3 consecutive years and funded his degree study with Book prizes, Study awards, bursaries and tuition. He has worked in Defence, Electronics and Semiconductor Industries. His current interests include Machine Learning, Deep Learning, Artificial Intelligence, Internet of Things, Robotics and Programming.

Dr. Alfred Ang was Distinguished Toastmasters (DTM) and Senior Member of IEEE. He has published more than 20 peer reviewed papers and co-inventors for more than 20 inventions.

Python TrainerDr. Yongxin (Steve) has more than five years of solid industrial and research experiences in data analytics. He held PdD on operations research in National University of Singapore. After his Phd study, he worked as data analyst and scientist in manufacturing and commodity trading companies. He is specialized in analyzing, visualizing and mining complex time series data using Python tools sucha as Pandas, Numpy, Matplotlib, SK-Learn, Tensorflow etc. He did research on predictive analytics on various systems e.g., Forex and commodity trading, system performance prediction, machine maintenance, etc. Besides data analytics using Python, he also extended his expertise in Microsoft Excel VBA, Hadoop big data platforms such as AWS and Microsoft Azure. In addition, he is strong in mathematical modelling and has cross-disciplinary domain knowledge in operations research, currency and commodity trading and industrial automation.

TrainerWee Chee Hong is a veteran consultant in the field of Engineering Design. He has over 20 years experience in electronics/ IT industry with several MNCs including Compaq, Adaptec, Agilent, etc., with specialization in Automation System Design (drilling/ milling machine, 3D machine automation, machine data collection, test & measurement electronics design), Motion control design & applications. With wide technical skill set in development language/ tools .Net, Java, PowerBuilder to C++/ C/C#, he has also strong knowledge in development of firmware for microcontroller such as PIC, ARM and others.

Chee Hong graduated with a B.Eng degree in Electrical Electronics Engineering and holds a Master Degree of Technology from NUS.

Python TrainerDr Brandon Ooi has a Bachelors degree in Computer Engineering and a PhD in Bioengineering from the National University of Singapore. He has published papers on machine learning, bioinformatics and microarray data analysis. He has six years of teaching experience at the polytechnic level and was also involved in the creation and teaching of modules for adult learners.

Python TrainerDr. Sarita Singh received her Ph.D. degree for her work done in the area of Information Security. She is the recipient of the prestigious Infosys fellowship for pursuing her Ph.D. Programme. She has more than twenty-five years of teaching and research experience in Singapore, Malaysia and India in the field of Programming, Information Security, Web-application Development, Computer Networks and Engineering related modules.

She has presented papers at several National and International Conferences and has written articles for magazines. She has authored text-books for Engineering courses as well.

Robotics Python TrainerMing Liang is an up-and-coming developer with expertise ranging from deep learning to hardware like the raspberry pi. He specialises mostly in the area of data science and machine learning and has won several hackathons and is ranked highly in international competitions. Furthermore, he has also done projects as part of the maker community in Singapore and build his own 3D printer as well

Big Data TrainerSunny Prakash is a Big Data Architect with Programming Background . He has around 7 years of IT experience. He has worked on Various Enterprise level solution. He is skilled in Cloud computing and Big Data Solution building in various Industrial sector and domain.

With an Strong background in Coding skills, he has a strong grips on Java,Python ,Scala ,HTML,JavaScript, Node Programming. Data Science is another specification where he has worked with larger Enterprises for finding their Data Insight and building Machine Learning mode

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