Nvidia Opens the Door to Deep Learning Workshops
Good news for folks looking to learn about the latest AI development techniques: Nvidia is now allowing the general public to access the online workshops it provides through its Deep Learning Institute (DLI). The GPU giant today announced today that selected workshops in the DLI catalog will be open to everybody. These workshops previously were […]
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Intuitive Intro To Generative Adversarial Networks – GAN Course Preview
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Frank
- July 26, 2021
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GANS
- generative adversarial networks
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard has a brand new premium course, an Introduction to Generative Adversarial Networks (GANs). Below is the full first lesson of the course available as a preview to the course at large.
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Intro to Generative Adversarial Networks (GANs) – New Course Release
-
Frank
- July 19, 2021
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GANS
- generative adversarial networks
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard announces their brand new premium deeplizard course, an Introduction to Generative Adversarial Networks (GANs)
Read More%20–%20New%20Course%20Release){kind=link}
NVIDIA ISC21 Special Address
NVIDIA provides an in-depth overview of the latest news, innovations, and technologies in AI supercomputing from Marc Hamilton, VP of Solutions Architecture and Engineering.
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NVIDIA CEO Jensen Huan on the Industrial HPC Revolution
Industrial high performance computing (HPC) is at its tipping point. The combination of simulation, accelerated computing, and #AI are bringing the performance and scale required to tackle real-world, industrial problems. This presentation blew my mind.
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Convolutions in Deep Learning – Interactive Demo App
-
Frank
- June 6, 2021
- activation function
- AI
- artificial intelligence
- artificial neural network
- Autoencoders
- batch normalization
- Clustering
- CNN
- Convolutional Neural Network
- CUDA
- cuDNN
- data augmentation
- Deep Learning
- Education
- fine-tune
- GPU
- image classification
- Keras
- Learning
- Machine Learning
- neural net
- Neural Network
- Nvidia
- Python
- PyTorch
- relu
- Sequential model
- SGD
- Supervised Learning
- TensorFlow
- tensorflow.js
- TFJS
- train
- Training
- Transfer Learning
- Tutorial
- Unsupervised Learning
deeplizard explains the importance of convolutions in deep learning. In deep learning, convolution operations are the key components used in convolutional neural networks. A convolution operation maps an input to an output using a filter and a sliding window. Use the interactive demonstration below to gain a better understanding of this process.
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GTC 2021 Keynote with NVIDIA CEO Jensen Huang
NVIDIA CEO Jensen Huang delivers the #GTC21 keynote, where he introduced a number of amazing breakthroughs.
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An AI That Makes Dog Photos
Two Minute Papers explores the paper “Training Generative Adversarial Networks with Limited Data.”
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Gaming on a $60,000 Computer
Linus Tech Tips uses a $60,000 server as a gaming PC. There’s still time for Santa to load one in his sleigh for you. Just saying.
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Nvidia Researchers Introduce A Modular Primitive To Provide High-Performance Primitive Operations For Rasterization-Based Differentiable Rendering
Rendering is a complex process. Its differentiation cannot be uniquely defined; thus, a straightforward integration into neural networks is impossible. Differentiable rendering (DR) constitutes a family of techniques that tackle such integration for end-to-end optimization by obtaining useful gradients of the rendering process. Nvidia and Aalto University introduce a modular primitive to provide high-performance primitive […]
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