Intro to Deep Learning with NVIDIA GPU

วันที่ 2-4 กรกฎาคม 2562 (9.30น. – 16.30น.)

สถานที่ Faculty of Engineering, Chulalongkorn University

Pre-requisites

Must have technical knowledge in R and Python, understand basic Data Science, Machine Learning and AI algorithms, familiarity with basic programming fundamentals such as functions and variables

Your Certificate

You will receive an e-Certificate by NVIDIA Deep Learning Institute upon completion.

About the Course

This workshop teaches you to apply deep learning techniques to a range of computer vision tasks through a series of hands-on exercises. You will work with widely-used deep learning tools, frameworks, and workflows to train and deploy neural network models on a fully-configured, GPU accelerated workstation in the cloud.

After a quick introduction to deep learning, you will advance to building and deploying deep learning applications for image classification and object detection, followed by modifying your neural networks to improve their accuracy and performance, and finish by implementing the workflow that you have learned on a final project. At the end of the workshop, you will have access to additional resources to create new deep learning applications on your own.

Learn the latest techniques on how to design, train, and deploy neural network-powered machine learning in your applications. You’ll explore widely used open-source frameworks and NVIDIA’s latest GPU-accelerated deep learning platforms.

 

DLI Workshop Attendee Instructions:

You MUST bring your own laptop to this workshop.

WHAT YOU WILL LEARN

Course Outline

Introduction to Deep Learning with NVIDIA GPU in Computer Vision

 

3 days from 9AM - 4:30PM
 

DAY 1 - (JULY 2, 2019)

Platform: Keras on Google Colab

Prerequisite: Python programming

What is Deep Learning and what are Neural Networks? (90 mins) [Lecture]

  • Basics of Deep Learning

  • Training a Neural Network

Practical session I (90 mins) [Lab]

  • Create a Neural Network in Python

Introduction to convolution neural networks and recurrent neural networks (90 mins) [Lecture]

  • Intuition and building blocks

  • Types of convolutional neural networks

  • Types of recurrent neural networks

Practical session II (60 mins) [Lab]

  • Convolutional Neural Networks and Recurrent Neural Networks

Tips and tricks to training a neural network model (30 mins) [Lecture]

 

DAY 2 [DLI] (JULY 3, 2019)

Platform: DIGITS

NVIDIA Deep Learning Institute Fundamentals Training

Pre-requisite: MUST have technical background and basic understanding of Deep Learning concepts

Certificate: Participants will receive an e-certificate from Deep Learning Institute
 

Image Classification with DIGITS (120 min)

  • How to leverage deep neural networks (DNN) within the deep learning workflow

  • Process of data preparation, model definition, model training and troubleshooting, validation testing and strategies for improving model performance using GPUs.

  • Train a DNN on your own image classification application

Object Detection with DIGITS (120 min)

  • Train and evaluate an image segmentation network

Neutral Network Deployment with DIGITS and TensorRT (120 min)

  • Uses a trained DNN to make predictions from new data

  • Show different approaches to deploying a trained DNN for inference

  • learn about the role of batch size in inference performance as well as virus optimisations that can be made in the inference process

 

DAY 3 (JULY 4, 2019)

 

Intelligent Video Analytics with Deep Learning

Platform: Keras on Google Colab

Prerequisite: Python programming & 1st training day

 

  • Overview of Architectures for Computer Vision (90 min)

  • Lab 1: Image classification with Keras (60 min)

 

  • Deployment with Deepstream and TensorRT (30 min)

  • Lab 2: Deployment for classification and detection tasks (30 min)

 

  • Transfer learning techniques (30 min)

  • Lab 3-1: Model adaptation (30 min)

  • Lab 3-2: Advanced techniques for adaptation (30 min)

 

  • Video action recognition (15 min)

  • Lab 4: Video action recognition (30 min)

  • Jetson Demo: deployment on Jetson (15 min)

 

จัดโดย iTrain Asia

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