About the course

You will learn:

In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly.

  • Learn the fundamental techniques and tools required to train a deep learning model
  • Gain experience with common deep learning data types and model architectures
  • Enhance datasets through data augmentation to improve model accuracy
  • Leverage transfer learning between models to achieve efficient results with less data and computation
  • Build confidence to take on your own project with a modern deep learning framework

Course Outline:

> Meet the instructor
> Create an account at nvidia.com

Explore the fundamental mechanics and tools involved in successfully
training deep neural networks:
> Train your first computer vision model to learn the process of training.
> Introduce convolutional neural networks to improve accuracy of predictions in vision applications.
> Apply data augmentation to enhance a dataset and improve
model generalization.

Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data:
> Integrate a pre-trained image classification model to create an
automatic doggy door.
> Leverage transfer learning to create a personalized doggy door that only lets in your dog.
> Train a model to autocomplete text based on New York Times headlines.

Apply computer vision to create a model that distinguishes between fresh and rotten fruit:

> Create and train a model that interprets color images.
> Build a data generator to make the most out of small datasets.
> Improve training speed by combining transfer learning and feature
extraction.
> Discuss advanced neural network architectures and recent areas of
research where students can further improve their skills.

> Review key learnings and answer questions.
> Complete the assessment and earn a certificate.
> Complete the workshop survey
> Learn how to set up your own AI application development environment.

Continue your learning with these DLI trainings:
>> Getting Started with Image Segmentation
>> Modeling Time-Series Data with Recurrent Neural Networks in Keras
>> Building Transformer-Based Natural Language Processing
Applications
>> Building Intelligent Recommender Systems
>> Fundamentals of Deep Learning for Multi-GPUs

If you are...

  • Developer
  • Data scientists
  • Data engineers

...this course is for you!

Why Choose NVIDIA Deep Learning Institute for Hands-On Training

Reason #1

Access workshops from anywhere with just your desktop/laptop computer and an internet connection. Each participant will have access to a fully configured, GPU-accelerated server in the cloud.

Reason #2

Obtain hands-on experience with the most widely used, industry-standard software, tools, and frameworks.

Reason #3

Learn to build deep learning and accelerated computing applications for industries, such as healthcare, robotics, manufacturing, accelerated computing, and more.

Reason #4

Gain real-world expertise through content designed in collaboration with industry leaders, such as the Children’s Hospital of Los Angeles, Mayo Clinic, and PwC.

Reason #5

Earn an NVIDIA Deep Learning Institute certificate to demonstrate your subject matter competency and support your career growth.