Do you know how easy it can be to apply Deep Learning with just a few lines of MATLAB code?

Yes, you can apply deep learning techniques to your work, from standard architectures for image and signal processing to advanced neural networks for a wide range of tasks. Join our webinar and workshop to learn how automation can help you label your data more efficiently, and how optimization techniques for hyperparameters can be used to maximize the performance of your networks.

Learn from our engineers and guest speakers from MathWorks who will share how companies worldwide are applying MATLAB and deep learning techniques to their projects in various industries.

Session #1: Deep Learning Overview

Overview

Deep Learning is a key technology driving the current Artificial Intelligence (AI) megatrend. You may have heard of some mainstream applications of deep learning, but how many of them would you consider to your engineering and science applications? MathWorks developers have purposely built MATLAB's deep learning functionality for engineering and science workflows. We understand that success goes beyond just developing a deep learning model. Ultimately, models need to be incorporated into an entire system design workflow to deliver a product or a service to the market.

Highlights:

• Introduction and Invite for the remaining sessions + Workshop

• Deep learning applications in engineering and science

• Workflow for researching, developing & deploying your deep learning application

• How to get started with deep learning in MATLAB

Registration for this session is closed now!! You can register with corporate details to watch it on demand recording.

Session #2: Automated and Iterative Labeling for Images and Signals by Dr. Rishu Gupta, Senior Application Engineer, MathWorks Inc.

Overview

In this session, we will be introducing the signal, image and video labelers and discuss the ways on how to extend these tools to facilitate labeling imagery to build AI models. We will be describing the use of preprocessing to facilitate the extraction of information from images, and present approaches to building models in an iterative fashion, validating predicted labels and incorporating on-the-fly models to label more and more data. In addition, we will discuss an approach to automating pixel-level labeling for semantic segmentation workflows.

Highlights:

• Using and Extending the Signal, Image and Video Labelers

• Preprocessing to facilitate image labeling

• Iteratively building and incorporating computer-vision and machine-learning models

• Automating pixel-level labeling
  
  

Registration for this session is closed now!! You can register with corporate details to watch it on demand recording.

Session #3: Deep Dive - Designing Experiments with AWS and Azure

Overview

Take a deeper dive into designing, training, and tuning deep learning models. Learn how MATLAB® deep learning apps can help you edit neural networks and devise and run experiments. See a brief teaser on how to customize deep learning training to handle more advanced types of neural networks.

You’ll be able to:

• Set up your AWS Cloud and Azure Cloud
• Use and Leverage cloud compute resources to speed up your training
• Compare results of on laptop vs. on cloud resources

Highlights:

• How to setup your MATLAB to Connect with AWS or Azure
• Using the Deep Network Designer app to graphically create, edit, and train models
• Tracking and running modeling runs with the Experiment Manager app for rapid, automated iteration
• Introducing the extended deep learning framework to customize and train advanced neural networks

Registration for this session is closed now!! You can register with corporate details to watch it on demand recording.

Session #4: Deploying your Deep Learning Models to Production

Overview

You’ve developed your algorithm, trained your deep learning model, and optimized it for the best performance possible. What’s next? In this session, you'll learn how to:

• Deploy on Embedded GPUs
• Deploy on to Website (MATLAB Production Server)
• Deploy to a Desktop
• Deploy on MCU

Registration for this session is closed now!! You can register with corporate details to watch it on demand recording.

Session #5: Deep Learning Hands-On Workshop (Limited Free Seats*) - CLOSED

Overview

Artificial Intelligence techniques like deep and machine learning are introducing automation to the products we build, processes we develop and the way we do business. You can use these techniques to solve complex problems related to images, signals, text and controls.

In this hands-on workshop, you will write code and use MATLAB Online to:

• Train deep neural networks on GPUs in the cloud
• Design deep neural networks using MATLAB’s interactive apps
• Explore Deep Learning techniques to work with images, time series, and text data

*Terms and Conditions:

• Due to the limited availability of seats, early registration is strongly recommended to ensure your participation.
• Registration will be confirmed upon your receipt of the confirmation, on a first-come-first-serve basis.
• Should you wish to cancel your registration, please inform us in writing to events@techsource-asia.com
• TechSource reserves the right to reschedule or cancel the event due to unforeseen circumstances. Every effort, however, will be made to inform participants of the change.