Practical Deep Learning with Bayesian Principles
Osawa et al.: https://arxiv.org/pdf/1906.02506.pdf
#Bayesian #DeepLearning #PyTorch #VariationalInference

✴️ @AI_Python_EN

This is probably the best #PyTorch Deep Learning course I have encountered.
https://fleuret.org/dlc/

✴️ @AI_Python_EN

An easy to follow and inspirational Blog about #PyTorch internals.
https://lnkd.in/efSEwpP

✴️ @AI_Python_EN

Why 2019 is the year of Knowledge Graphs?
✔️#Knowledgegraph became a centerpiece of #Accentur and #Microsoft ’s toolkits.

✔️Knowledge graph lessons from Google, #Facebook, #eBay, #IBM.

✔️Graph algorithms and analytics by #Neo4j, #Nvidia and #AWS.

More about the why?
https://lnkd.in/g87BTrH

💥Great resources to get some hands-on experience:

✅ Implementing Knowledge Graphs in #Enterprises:
https://lnkd.in/ghisXMw

✅ How #Google’s Knowledge Graph Updates Itself:
https://lnkd.in/gayCpPw

✅ Extracting knowledge from knowledge graphs using #Facebook #Pytorch BigGraph.
https://lnkd.in/gHgj6AH

✅ The Data Fabric for #MachineLearning : #DeepLearning on Graphs. By Favio Vazquez
https://lnkd.in/gsCnTTM

✅ Why Knowledge Graphs Are Foundational to #ArtificialIntelligence
https://lnkd.in/g5WVARe

Absolutely essential for data scientists to upskill themselves, Knowledge Graphs are coming...
#datascience #AI

✴️ @AI_Python_EN

Getting System Information in Linux using Python Script.
#BigData #Analytics #DataScience #IoT #PyTorch #Python #RStats #TensorFlow #DataScientist #Linux

http://bit.ly/2X56cZa

✴️ @AI_Python_EN

This is the reference implementation of Diff2Vec - "Fast Sequence Based Embedding With Diffusion Graphs" (CompleNet 2018). Diff2Vec is a node embedding algorithm which scales up to networks with millions of nodes. It can be used for node classification, node level regression, latent space community detection and link prediction. Enjoy!

https://lnkd.in/dXiy5-U

#technology #machinelearning #datamining #datascience #deeplearning #neuralnetworks #pytorch #tensorflow #diffusion #Algorithms

✴️ @AI_Python_EN

PyTorchPipe (PTP)

A component-oriented framework for rapid prototyping and training of computational pipelines combining vision and language:
https://lnkd.in/ehJbseR

#PyTorch #NeuralNetworks #DeepLearning

✴️ @AI_Python_EN

https://lnkd.in/e2awdVx
Not to be confused with (https://lnkd.in/eydGDPu), mmdetection supports all the SOTA detection algorithms.
#pytorch #gpu

✴️ @AI_Python_EN

Interesting work from Ross Wightman comparing something like EfficientNet / ResNet which uses only Imagenet data to the Facebook-IG ResNext that was trained on a lot of instagram public data. While their validation scores are close, the test scores seem to diverge more.

FacebookAI ResNeXt models pre-trained on Instagram hashtags stand out in their ability to generalized to the 'ImageNetV2' test set.
#PyTorch
https://colab.research.google.com/github/rwightman/pytorch-image-models/blob/master/notebooks/GeneralizationToImageNetV2.ipynb

✴️ @AI_Python_EN

One of the best resources for #PyTorch based #pretrained CNN models.
https://lnkd.in/eY87mFf

✴️ @AI_Python_EN

Pytorch Implementation of Deep Flow.

#BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #TensorFlow #CloudComputing #DataScientist #Linux

https://arxiv.org/pdf/1905.02884.pdf

✴️ @AI_Python_EN

#Detection ...? or #Classification ...? its all there in #PyTorch.
A pytorch lib with state-of-the-art architectures, pre-trained models and real-time updated results.
#deeplearning #ai #cnn

https://lnkd.in/eTdvfEp

✴️ @AI_Python_EN

PyTorch implementations of deep reinforcement learning algorithms and environments

GitHub, by Petros Christodoulou : https://lnkd.in/eRZCQ-d

#pytorch #reinforcementlearning #deeplearning

How #Facebook used Mask R-CNN, #PyTorch, and custom hardware integrations like foveated processing to improve Portal’s Smart Camera system.

Link:
https://ai.facebook.com/blog/smart-camera-portal-advances/

#CV #DL #Segmentation

Understanding the Backpropagation Algorithm.

#BigData #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #TensorFlow #CloudComputing #Algorithms

http://bit.ly/2ASKwqx

❇️ @AI_Python_EN

Spooky Lavanya

Weights & Biases is officially included in Stanford's CS 197 class!

I wrote a quick tutorial on how to train a neural network using #PyTorch & track your experiments in W&B!
Class:
http://cs197.stanford.edu/assignments/a3.shtml
Code:
https://colab.research.google.com/drive/1zkoPdBZWUMsTpvA35ShVNAP0QcRsPUjf

#MachineLearning

❇️ @AI_Python_en

The war between ML frameworks has raged on since the rebirth of deep learning. Who is winning? Horace He data analysis shows clear trends: PyTorch is winning dramatically among researchers, while Tensorflow still dominates industry.
#PyTorch #Tensorflow

https://thegradient.pub/state-of-ml-frameworks-2019-pytorch-dominates-research-tensorflow-dominates-industry/

❇️ @AI_Python_EN

Pytorch-Struct

Fast, general, and tested differentiable structured prediction in PyTorch. By Harvard NLP : https://lnkd.in/e2iGiNa

#PyTorch #DeepLearning #ArtificialIntelligence

✴️ @AI_Python_EN

"Differentiable Convex Optimization Layers"

CVXPY creates powerful new PyTorch and TensorFlow layers

Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/

#PyTorch #TensorFlow #NeurIPS2019


❇️ @AI_Python_EN

New State of the Art AI Optimizer: Rectified Adam (RAdam) Improve your AI accuracy instantly versus Adam, and why it works. Blog by Less Wright :

https://medium.com/@lessw/new-state-of-the-art-ai-optimizer-rectified-adam-radam-5d854730807b

#MachineLearning #TensorFlow #Pytorch #DeepLearning

❇️ @AI_Python_EN