- December 2, 2021
- 10:00 AM - 2:00 PM
Deep Learning - Module 2
Dec, 2nd 2021
10:00 AM – 2:00 PM
Deep Learning – Module 2
DEVELOPMENT OF ADVANCED DEEP NEURAL ARCHITECTURE AND EMBEDDED DEPLOYMENT
This workshop is in association with:
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 applying to your engineering and science applications?
In this workshop, we will take a deeper dive into designing, customizing, and training and hyperparameter of advanced neural networks. We will show how MATLAB’s deep learning apps can help you edit neural networks, and devise and run experiments. We will give detail workflow on how to customize deep learning training to handle more advanced types of neural networks. Also, once the network is developed, we need to deploy the networks on different platforms and to address that we would talk about automatic code generation and embedded deployment of Deep learning models on embedded or edge devices
Program Objectives
- Using the Deep Network Designer app to graphically create, edit, and train models.
- Introducing the extended deep learning framework to customize and train advanced neural networks.
- Generating realistic synthetic image data with GANs.
- Implementing generalized research models in MATLAB.
- Generate C/C++ or CUDA code from deep learning networks as inference engines for NVIDIA GPUs, Intel Xeon CPUs, or ARM Cortex-A processors.
Learning Outcomes
- Gain knowledge and insight about artificial intelligence and Deep learning as a technology.
- Learn about MATLAB’s end-to-end workflow from development to deployment for AI applications
- Capability to use MATLAB for addressing AI challenges around
- Data Labelling
- Hyperparameter tuning
- Embedded deployment
Workshop Schedule
Hands-on Deep Learning virtual workshop for images
To get a hands-on appreciation for Deep Learning with MATLAB, register to attend the free 3-hour Virtual Lab. Learn to solve complex problems related to signals with Deep Learning on MATLAB.
Guided by a team of professional engineers, you will write code using MATLAB Online to:
- Train deep neural networks on GPUs in the cloud.
- Create Deep Learning models from scratch for image and signal data.
- Explore pretrained models and use transfer learning.
- Import and export models from Python frameworks such as Keras and PyTorch.
- Automatically generate code for embedded targets.
No installation of MATLAB is necessary. Please make sure you have a strong internet connection to ensure optimal experience.
Who should attend?
Anybody who is
- working on artificial intelligence/deep learning applications
- looking forward to exploring artificial intelligence and deep learning as a domain
- interested to learn about Deep learning and Artificial intelligence using MATLAB
About the Speaker
Dr. Rishu Gupta
Senior application Engineer, MathWorks India.
Dr. Rishu Gupta is a senior application engineer at MathWorks India. He primarily focuses on image processing, computer vision, and deep learning applications. Rishu has over nine years of experience working on applications related to visual contents. He previously worked as a scientist at LG Soft India in the Research and Development unit. He has published and reviewed papers in multiple peer-reviewed conferences and journals. Rishu holds a bachelor’s degree in electronics and communication engineering from BIET Jhansi, a master’s in visual contents from Dongseo University, South Korea, working on the application of computer vision, and a Ph.D. in electrical engineering from University Technology Petronas, Malaysia with a focus on biomedical image processing for ultrasound images.