[D] Where can I find pre-trained GANs for TensorFlow? • r/MachineLearning

#artificialintelligence

I'm finding it very hard to find online any GAN model source code which comes with pre-trained parameters. Specifically, I'm interested in image generation (from random noise input), trained on a "challenging" data set such as ImageNet (even if downsampled...) (I'm less interested in MNIST...)


Approach pre-trained deep learning models with caution

#artificialintelligence

It seems like using these pre-trained models have become a new standard for industry best practices. After all, why wouldn't you take advantage of a model that's been trained on more data and compute than you could ever muster by yourself? Advances within the NLP space have also encouraged the use of pre-trained language models like GPT and GPT-2, AllenNLP's ELMo, Google's BERT, and Sebastian Ruder and Jeremy Howard's ULMFiT (for an excellent over of these models, see this TOPBOTs post). One common technique for leveraging pretrained models is feature extraction, where you're retrieving intermediate representations produced by the pretrained model and using those representations as inputs for a new model. These final fully-connected layers are generally assumed to capture information that is relevant for solving a new task.


Object Detection with TensorFlow and Smalltalk

#artificialintelligence

In a previous post we saw basic object recognition in images using Google's TensorFlow library from Smalltalk. This post will walk you step by step through the process of using a pre-trained model to detect objects in an image. It may also catch your attention that we are doing this from VASmalltalk rather than Python. Check out the previous post to see why I believe Smalltalk could be a great choice for doing Machine Learning. We provide a collection of detection models pre-trained on the COCO dataset, the Kitti dataset, the Open Images dataset, the AVA v2.1 dataset and the iNaturalist Species Detection Dataset.



Choosing an Open Source Machine Learning Library: TensorFlow, Theano, Torch, scikit-learn, Caffe

#artificialintelligence

From healthcare and security to marketing personalization, despite being at the early stages of development, machine learning has been changing the way we use technology to solve business challenges and everyday tasks. This potential has prompted companies to start looking at machine learning as a relevant opportunity rather than a distant, unattainable virtue. We've already discussed machine learning as a service tools for your ML projects. But now let's look at free and open source software that allows everyone to board the machine learning train without spending time and resources on infrastructure support. The term open source software refers to a tool with a source code available via the Internet for free.