The best way to learn #DeepLearning is by practicing it. But which framework to use? Here are 5 articles to get you started!

A Comprehensive Introduction to #PyTorch - https://bit.ly/2L8Rj7n

Learn How to Build Quick & Accurate Neural Networks using PyTorch (& 4 Case Studies) - https://bit.ly/2Vts9nY

Get Started with Deep Learning using #Keras and #TensorFlow in #R - https://bit.ly/2Iro2BY

TensorFlow 101: Understanding Tensors and Graphs - https://bit.ly/2GNg195

An Introduction to Implementing #NeuralNetworks using TensorFlow - https://bit.ly/2V17cBs

✴️ @AI_Python_EN

Swift + TensorFlow

Create a simple NN and CNN.

Notebook by Zaid Alyafeai: https://lnkd.in/e5zWxZ5

#ArtificialIntelligence #DeepLearning #NeuralNetworks

✴️ @AI_Python_EN

Activation Atlases: a new technique for visualizing what interactions between neurons can represent

By Google and OpenAI.

Blog: https://blog.openai.com/introducing-activation-atlases/
Paper: https://distill.pub/2019/activation-atlas
Code: https://github.com/tensorflow/lucid/…
Demo: https://distill.pub/2019/activation-atlas/app.html

#artificialintelligence #deeplearning #machinelearning #neuralnetworks

✴️ @AI_Python_EN

Walkthrough - When and How to Use MLP, CNN, and RNN Neural Networks - Jason Brownlee

To follow posts: https://lnkd.in/ev9S2hh

#machinelearning #artificialintelligence #datascience #ml #ai #deeplearning #MLP #CNN #RNN #neuralnetworks

✴️ @AI_Python_EN

Google Machine Learning (101 slides) - Jason Mayes

posts: https://lnkd.in/ev9S2hh

#machinelearning #artificialintelligence #datascience #ml #ai #DeepLearning #BigData #NeuralNetworks #Algorithms #DataScientists #ReinforcementLearning

✴️ @AI_Python_EN

A Very Short History of Artificial Neural Networks

🌎 History of Artificial Neural Networks

#ArtificialNeuralNetwork #neuralnetworks #ReinforcementLearning #ANN #NN

✴️ @AI_Python_EN

Can #neuralnetworks be made to reason?" Conversation with Ian Goodfellow

Full version: https://www.youtube.com/watch?v=Z6rxFNMGdn0


✴️ @AI_Python

Understanding Neural Networks via Feature Visualization: A survey

Nguyen et al.: https://lnkd.in/eRZMuTS

#neuralnetworks #generatornetwork #generativemodels

✴️ @AI_Python_EN

ery interesting paper on machine learning algorithms. This paper compares polynomial regression vs neural networks applying on several well known datasets (including MNIST). The results are worth looking.

Other datasets tested: (1) census data of engineers salaries in Silicon Valley; (2) million song data; (3) concrete strength data; (4) letter recognition data; (5) New York city taxi data; (6) forest cover type data; (7) Harvard/MIT MOOC course completion data; (8) amateur athletic competitions; (9) NCI cancer genomics; (10) MNIST image classification; and (11) United States 2016 Presidential Election.

I haven't reproduced the paper myself but I am very tempted in doing it.

Link here: https://lnkd.in/fd-VNtk

#machinelearning #petroleumengineering #artificialintelligence #data #algorithms #neuralnetworks #predictiveanalytics

✴️ @AI_Python_EN

The Deep Learning Toolset — An Overview

http://bit.ly/2R2eUGh

#artificialintelligence, #bigdata, #businessanalytics, #datascience, #deeplearning, #ds #datascience, #iot, #machinelearning, #neuralnetworks #AI

✴️ @AI_Python_EN

Deep Learning: AlphaGo Zero Explained In One Picture

By L.V.: https://lnkd.in/eJMAKfy

#ArtificialIntelligence #DeepLearning #NeuralNetworks #ReinforcementLearning

✴️ @AI_Python_EN

Convolutional #NeuralNetworks (CNN) for Image Classification — a step by step illustrated tutorial: https://dy.si/hMqCH
BigData #AI #MachineLearning #ComputerVision #DataScientists #DataScience #DeepLearning #Algorithms

✴️ @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

bit.ly/2JeYsQr
Demystifying the Math Behind Neural Nets — learn how #NeuralNetworks Learn, with an implementation demonstrated one step at a time:
http://bit.ly/2JgmGKh

✴️ @AI_Python_EN

Towards Declarative Visual Reasoning… Or Not? https://buff.ly/2UkT3u4
#NeuralNetworks #DeepLearning #AI

Deep Learning course: lecture slides and lab notebooks

https://m2dsupsdlclass.github.io/lectures-labs/

#ArtificialIntelligence #DeepLearning #GenerativeAdversarialNetworks #MachineLearning #NeuralNetworks

❇️ @AI_Python_EN

Memory Augmented Recursive Neural Networks
Arabshahi et al.:

https://arxiv.org/abs/1911.01545

#ArtificialIntelligence #MachineLearning #NeuralNetworks

❇️ @AI_Python_EN

Mish is now even supported on YOLO v3 backend. Couldn't have been more elated with how rewarding this project has been. Link to repository -

https://github.com/digantamisra98/Mish

#neuralnetworks #mathematics #algorithms #deeplearning #machinelearning

❇️ @AI_Python_EN

Evolving Neural Networks
A tutorial on evolutionary algorithms

https://towardsdatascience.com/evolving-neural-networks-b24517bb3701

#NeuralNetworks #ReinforcementLearning

❇️ @AI_Python_EN