This post presents a snapshot of the system status in mid-2020 and highlights some of the work done by the PilotNet group.
This post presents a snapshot of the system status in mid-2020 and highlights some of the work done by the PilotNet group.
Category: Misc
In this three-part series, you discover how to use NVIDIA Nsight Compute for iterative, analysis-driven optimization.
In this three-part series, you discover how to use NVIDIA Nsight Compute for iterative, analysis-driven optimization. Part 1 covers the background and setup needed, part 2 covers beginning the iterative optimization process, and part 3 covers finishing the analysis and optimization process and determining whether you have reached a reasonable stopping point.
In this post, we discuss the various considerations for enabling Tensor Cores in NVIDIA libraries.
In this post, we discuss the various considerations for enabling Tensor Cores in NVIDIA libraries.
We love PC games. The newest titles and the greatest classics. FPS, RPG, grand strategy, squad-based tactics, single-player, multiplayer, MMO — you name it, we love it. There are more than 800 games on GeForce NOW — including 80 of the biggest free-to-play games — streaming straight from the cloud. And thanks to the explosive Read article >
The post New Games, New Features — That’s GFN Thursday appeared first on The Official NVIDIA Blog.
Hey! Sorry, if this question does not make 100% sense as my
education has not yet reached formal ML classes, but I’ll ask
nonetheless.
I want to make a GAN in tensorflow, but instead of just copy and
pasting someone’s code, I want to truly understand the bits and
parts of it.
From what I know about Naive Bayes, it predicts the distribution
of our original data – but after each iteration how can one sample
from this distribution, and additionally once you take a sample
from this distribution, how can we actually in code pass it to our
discriminator?
Thanks everyone 🙂
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Image segmentation and recommender system Jupyter notebooks are now available in the NGC catalog. These Jupyter notebooks come with complete instructions on how to train these models using the resources from the NGC catalog.
Image segmentation and recommender system Jupyter notebooks are now available in the NGC catalog. These Jupyter notebooks come with complete instructions on how to train these models using the resources from the NGC catalog.
Upcoming Webinars
The NVIDIA NGC team is hosting two webinars with live Q&A to dive into two new Jupyter notebooks available from the NGC catalog. Learn how to use these resources to kickstart your AI journey.
NVIDIA NGC Jupyter Notebook Day: Image Segmentation
February 18 at 9 a.m. PT
Image segmentation deals with placing each pixel of an image into specific classes that share common characteristics.
In this session, you’ll learn:
- How to use a Jupyter notebook containing a pre-trained image segmentation model that can be used to detect defective parts in an industrial application
- How to refine the model by retraining the model using your own hyperparameters and test it using your own checkpoints
NVIDIA NGC Jupyter Notebook Day: Recommender System
February 18 at 11 a.m. PT
Recommender systems deal with predicting user preferences for products based on historical behavior or actions and are widely used in online retail, social media, streaming video, music platforms, and more.
In this session, you’ll learn:
- How to leverage a Jupyter notebook containing a pre-trained recommender system model that can be used to recommend a movie based on a user’s viewing history
- How to refine the model by retraining the model using your own hyperparameters and test it using your own checkpoints
Categories
Constrain outputs in a regression problem
Hi, everyone.
I am attempting to constrain some outputs of my regression
network, say x, y, z = model(data), where x, y, z are scalars. The
constrain that I want to impose is that when predicting all three
dependent variables, the condition “x + y <=1.0” must be
honored. Given this description, can I implement this in a forward
function?
Thank you!
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Categories
Tool for Complex Data Labelling Tasks
Hi /r/tensorflow
readers!
We have created a labelling
tool that can be customized to display all sorts of data models
and tasks. Here are a couple of examples for NLP
and CV.
I hope some of you will find this useful, and if you have any
thoughts I would love to hear your feedback!
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