Lab Catalog

The NVIDIA Deep Learning Institute (DLI) offers hands-on training for developers, data scientists, and researchers on how to design, train, and deploy neural networks across a variety of application domains, including Autonomous Vehicles, Healthcare, IVA, Robotics, and more. Take a self-paced lab today or choose from our list of labs below to customize a workshop for your team or organization.

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Applications of Deep Learning with Caffe, Theano and Torch

Gain an understanding of GPU-accelerated deep learning and learn which deep learning software frameworks are right for you.
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Image Classification with DIGITS

Learn how to leverage deep neural networks (DNN) within the deep learning workflow to solve a real-world image classification problem using NVIDIA DIGITS™.
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Object Detection with DIGITS

Explore three approaches to identifying a specific feature within an image using neural networks trained on NVIDIA DIGITS.
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Image Segmentation with TensorFlow

Explore how to train and evaluate an image segmentation network with TensorFlow, using the Sunnybrook cardiac MRI dataset to identify the left ventricle of a human heart.
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Signal Processing with NVIDIA DIGITS

Learn how to process data from sensors such as acoustic, seismic, radio, and radar by leveraging NVIDIA DIGITS to train and test a Convolutional Neural Network (CNN).
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Neural Network Deployment with DIGITS and TensorRT

Explore three approaches for deployment using DIGITS, Caffe, and NVIDIA TensorRT™. Plus, understand the role of batch size in inference performance and which optimizations can be made in the inference process.
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Linear Classification with Tensorflow

Learn to use the TF.Learn API in Tensorflow to train and evaluate a linear model to predict individual income based on census data.
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Deep Learning Workflows with TensorFlow, MXNet and NVIDIA-Docker

Get experience working with Docker images and managing the container lifecycle, plus learn step-by-step examples of deep learning training in both TensorFlow and MXNet using nvidia-docker.
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Photo Editing with Generative Adversarial Networks with Tensorflow and DIGITS

Learn how to train a GAN to generate images of handwritten digits in DIGITS using the MNIST dataset, then apply them on the CelebA dataset of celebrity faces.


Deep Reinforcement Learning Agents on Atari 2600 Games

Learn the basic principles of reinforcement learning and develop a learning agent capable of playing classic Atari games.


Modeling Time Series Data with Recurrent Neural Networks in Keras

Learn how to create training and testing datasets using electronic health records and prepare datasets for use with RNNs.
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Medical Image Analysis with R and MXNet

Explore how to detect features indicative of medical conditions by using MxNet to train a CNN to infer the volume of the left ventricle of the human heart.
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Image Recognition with CNTK

Understand how to use CNTK from Microsoft for training and testing neural networks to recognize handwritten digits.


Medical Image Segmentation using DIGITS

Learn how to use popular image classification neural networks for semantic segmentation using Sunnybrook Cardiac Data to train a neural network to locate the left ventricle on MRI images.
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Image Classification with TensorFlow: Radiomics - 1p19q Chromosone Status Classification with Deep Learning

Learn how to detect the 1p19q co-deletion biomarker using deep learning (specifically CNNs) using Keras and TensorFlow in order to predict Radiomics.
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Deep Learning for Genomics using DragoNN with Keras and Theano

Explore using the dragonn toolkit on simulated and real regulatory genomic data, demystify popular DragoNN architectures and learn how to model and interpret regulatory sequence using DragoNN models.
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Deep Learning for Image and Video Captioning

Apply a deep learning technique via frameworks to generate captions based on image data.


From Trained Neural Network Model to Deployment for Inference

Get hands-on experience using TensorRT to optimize, validate, and deploy trained neural network for inference in a self-driving car application.


Image Classification and Object Detection with NVIDIA Jetson TX2

Learn how to take pre-trained image classification and object detection networks and deploy them on Jetson TX1 or TX2 Developer Kits.


Introduction and Integration with DriveWorks on Drive PX2

Get an introduction to DriveWorks and learn how to integrate DriveWorks modules into your custom code or applications.

GET STARTED WITH LABS FOR ALL INDUSTRIES


Applications of Deep Learning with Caffe, Theano and Torch

Gain an understanding of GPU-accelerated deep learning and learn which deep learning software frameworks are right for you.
Get Started>


Image Classification with DIGITS

Learn how to leverage deep neural networks (DNN) within the deep learning workflow to solve a real-world image classification problem using NVIDIA DIGITS™.
Get Started>


Object Detection with DIGITS

Explore three approaches to identifying a specific feature within an image using neural networks trained on NVIDIA DIGITS.
Get Started>


Image Segmentation with TensorFlow

Explore how to train and evaluate an image segmentation network with TensorFlow, using the Sunnybrook cardiac MRI dataset to identify the left ventricle of a human heart.
Get Started>


Signal Processing with NVIDIA DIGITS

Learn how to process data from sensors such as acoustic, seismic, radio, and radar by leveraging NVIDIA DIGITS to train and test a Convolutional Neural Network (CNN).
Get Started>


Neural Network Deployment with DIGITS and TensorRT

Explore three approaches for deployment using DIGITS, Caffe, and NVIDIA TensorRT™. Plus, understand the role of batch size in inference performance and which optimizations can be made in the inference process.
Get Started>


Linear Classification with Tensorflow

Learn to use the TF.Learn API in Tensorflow to train and evaluate a linear model to predict individual income based on census data.
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LEARN MORE WITH AUTONOMOUS VEHICLES LABS


From Trained Neural Network Model to Deployment for Inference

Get hands-on experience using TensorRT to optimize, validate, and deploy trained neural network for inference in a self-driving car application.


Introduction and Integration with DriveWorks on Drive PX2

Get an introduction to DriveWorks and learn how to integrate DriveWorks modules into your custom code or applications.


Join our five-day Autonomous Vehicles course to deep dive into the following topics:

  • Developer Tools for DRIVE PX2
  • Sensor Fusion with DriveWorks
  • Perception, Localization and Path Planning with DNNs
  • DNN Inference Optimization with TensorRT
  • Integration of DRIVE PX 2 on Development Car

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Applications of Deep Learning with Caffe, Theano and Torch

Gain an understanding of GPU-accelerated deep learning and learn which deep learning software frameworks are right for you.
Get Started>


Image Classification with DIGITS

Learn how to leverage deep neural networks (DNN) within the deep learning workflow to solve a real-world image classification problem using NVIDIA DIGITS™.
Get Started>


Object Detection with DIGITS

Explore three approaches to identifying a specific feature within an image using neural networks trained on NVIDIA DIGITS.
Get Started>


Image Segmentation with TensorFlow

Explore how to train and evaluate an image segmentation network with TensorFlow, using the Sunnybrook cardiac MRI dataset to identify the left ventricle of a human heart.
Get Started>


Signal Processing with NVIDIA DIGITS

Learn how to process data from sensors such as acoustic, seismic, radio, and radar by leveraging NVIDIA DIGITS to train and test a Convolutional Neural Network (CNN).
Get Started>


Neural Network Deployment with DIGITS and TensorRT

Explore three approaches for deployment using DIGITS, Caffe, and NVIDIA TensorRT™. Plus, understand the role of batch size in inference performance and which optimizations can be made in the inference process.
Get Started>


Linear Classification with Tensorflow

Learn to use the TF.Learn API in Tensorflow to train and evaluate a linear model to predict individual income based on census data.
Get Started>


LEARN MORE WITH HEALTHCARE LABS


Medical Image Segmentation using DIGITS

Learn how to use popular image classification neural networks for semantic segmentation using Sunnybrook Cardiac Data to train a neural network to locate the left ventricle on MRI images.
Get Started>


Modeling Time Series Data with Recurrent Neural Networks in Keras

Learn how to create training and testing datasets using electronic health records and prepare datasets for use with RNNs.
Get Started>


Learn more with our Full-Day Workshop: Deep Learning for Healthcare Genomics.

  • Image Classification with DIGITS

  • Image Classification with TensorFlow: Radiomics - 1p19q Chromosome Status Classification with Deep Learning
    Learn how to detect the 1p19q co-deletion biomarker using deep learning (specifically CNNs) using Keras and TensorFlow in order to predict Radiomics.

  • Deep Learning for Genomics using DragoNN with Keras and Theano
    Explore using the dragonn toolkit on simulated and real regulatory genomic data, demystify popular DragoNN architectures and learn how to model and interpret regulatory sequence using DragoNN models.


Learn more with our Full-Day Workshop: Deep Learning for Healthcare Image Analysis.

  • Medical Image Segmentation using DIGITS
    Learn how to use popular image classification neural networks for semantic segmentation using Sunnybrook Cardiac Data to train a neural network to locate the left ventricle on MRI images.

  • Medical Image Analysis with R and MXNet
    Explore how to detect features indicative of medical conditions by using MxNet to train a CNN to infer the volume of the left ventricle of the human heart.

  • Image Classification with TensorFlow: Radiomics - 1p19q Chromosome Status Classification with Deep Learning

GET STARTED WITH LABS FOR ALL INDUSTRIES


Applications of Deep Learning with Caffe, Theano and Torch

Gain an understanding of GPU-accelerated deep learning and learn which deep learning software frameworks are right for you.
Get Started>


Image Classification with DIGITS

Learn how to leverage deep neural networks (DNN) within the deep learning workflow to solve a real-world image classification problem using NVIDIA DIGITS™.
Get Started>


Object Detection with DIGITS

Explore three approaches to identifying a specific feature within an image using neural networks trained on NVIDIA DIGITS.
Get Started>


Image Segmentation with TensorFlow

Explore how to train and evaluate an image segmentation network with TensorFlow, using the Sunnybrook cardiac MRI dataset to identify the left ventricle of a human heart.
Get Started>


Signal Processing with NVIDIA DIGITS

Learn how to process data from sensors such as acoustic, seismic, radio, and radar by leveraging NVIDIA DIGITS to train and test a Convolutional Neural Network (CNN).
Get Started>


Neural Network Deployment with DIGITS and TensorRT

Explore three approaches for deployment using DIGITS, Caffe, and NVIDIA TensorRT™. Plus, understand the role of batch size in inference performance and which optimizations can be made in the inference process.
Get Started>


Linear Classification with Tensorflow

Learn to use the TF.Learn API in Tensorflow to train and evaluate a linear model to predict individual income based on census data.
Get Started>


LEARN MORE WITH IVA LABS


Deep Learning for Image and Video Captioning

Apply a deep learning technique via frameworks to generate captions based on image data.

GET STARTED WITH LABS FOR ALL INDUSTRIES


Applications of Deep Learning with Caffe, Theano and Torch

Gain an understanding of GPU-accelerated deep learning and learn which deep learning software frameworks are right for you.
Get Started>


Image Classification with DIGITS

Learn how to leverage deep neural networks (DNN) within the deep learning workflow to solve a real-world image classification problem using NVIDIA DIGITS™.
Get Started>


Object Detection with DIGITS

Explore three approaches to identifying a specific feature within an image using neural networks trained on NVIDIA DIGITS.
Get Started>


Image Segmentation with TensorFlow

Explore how to train and evaluate an image segmentation network with TensorFlow, using the Sunnybrook cardiac MRI dataset to identify the left ventricle of a human heart.
Get Started>


Signal Processing with NVIDIA DIGITS

Learn how to process data from sensors such as acoustic, seismic, radio, and radar by leveraging NVIDIA DIGITS to train and test a Convolutional Neural Network (CNN).
Get Started>


Neural Network Deployment with DIGITS and TensorRT

Explore three approaches for deployment using DIGITS, Caffe, and NVIDIA TensorRT™. Plus, understand the role of batch size in inference performance and which optimizations can be made in the inference process.
Get Started>


Linear Classification with Tensorflow

Learn to use the TF.Learn API in Tensorflow to train and evaluate a linear model to predict individual income based on census data.
Get Started>


LEARN MORE WITH ROBOTICS LABS


Image Classification and Object Detection with NVIDIA Jetson TX2

Learn how to take pre-trained image classification and object detection networks and deploy them on Jetson TX1 or TX2 Developer Kits.


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