Recurrent Neural Networks for Edge Intelligence: A Survey #Survey #RNN @Machine_learn

#RNN #Slide and #Survey @Machine_learn

GoEmotions: A Dataset for Fine-Grained Emotion Classification


http://ai.googleblog.com/2021/10/goemotions-dataset-for-fine-grained.html

@Machine_learn

🔊 Torchaudio: an audio library for PyTorch

Github: https://github.com/pytorch/audio

Paper: https://arxiv.org/abs/2110.15018v1

Dataset: https://paperswithcode.com/dataset/ljspeech

@Machine_learn

The fashion industry is on the verge of an unprecedented change. The implementation of machine learning, computer vision, and artificial intelligence (AI) in fashion applications is opening lots of new opportunities for this industry. This paper provides a comprehensive survey on this matter, categorizing more than 580 related articles into 22 well-defined fashion-related tasks. Such structured task-based multi-label classification of fashion research articles provides researchers with explicit research directions and facilitates their access to the related studies, improving the visibility of studies simultaneously. For each task, a time chart is provided to analyze the progress through the years. Furthermore, we provide a list of 86 public fashion datasets accompanied by a list of suggested applications and additional information for each.
link: https://arxiv.org/abs/2111.00905

@Machine_learn

COMPARATIVE STUDY OF CAPSULE NEURAL NETWORK IN VARIOUS APPLICATIONS #CapsuleNet #Paper #Survey @Machine_learn

An overview over Capsule Networks #CapsuleNet #Paper #survey @Machine_learn

MetNet-2: Deep Learning for 12-Hour Precipitation Forecasting


http://ai.googleblog.com/2021/11/metnet-2-deep-learning-for-12-hour.html

@Machine_learn

Code:
https://github.com/gist-ailab/uoais#unseen-object-amodal-instance-segmentation-uoais

Paper:
https://arxiv.org/abs/2109.11103

Dataset:
https://paperswithcode.com/dataset/ocid

Project page:
https://sites.google.com/view/uoais


@Machine_learn

What is Twitter, a Social Network or a News Media #Twitter #Paper @Machine_learn

Social Networks and Microblogging;The Emerging Marketing
Trends&Tools of the Twenty-first Century #Twitter #Paper @Machine_learn

Twitter as a Tool for Health Research:
a Systematic Review #Paper #Twitter @Machine_learn

Sentiment Analysis of Twitter Messages Using Word2Vec #Twitter #Paper @Machine_learn

Public Sentiment Analysis in Twitter Data for
Prediction of A Company’s Stock Price Movements #Twitter #Paper @Machine_learn

The impact of microblogging data for stock market prediction: Using
Twitter to predict returns, volatility, trading volume and survey
sentiment indices #Twitter #Paper @Machine_learn

با عرض سلام تخفیف پکیچ کدنویسی ما برای دوستان. هزینه این پکیچ با تخفیف 300 هزار می باشد و برای دوستانی که بضاعت مالی دارند باز هم تخفیف خواهیم داد. جهت دریافت به ایدی بنده پیام بدین @Raminmousa

Predicting Text Selections with Federated Learning


http://ai.googleblog.com/2021/11/predicting-text-selections-with.html

@Machine_learn

Introducing TensorFlow Graph Neural Networks

A new API for TF2 to build GNNs. It would be interesting to see how it compares to PyG and DGL libraries.
@Machine_learn

An important collection of the 15 best machine learning cheat sheets.
1- Supervised Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf

2- Unsupervised Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf

3- Deep Learning

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-learning.pdf

4- Machine Learning Tips and Tricks

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf

5- Probabilities and Statistics

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf

6- Comprehensive Stanford Master Cheat Sheet

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf

7- Linear Algebra and Calculus

https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf

8- Data Science Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf

9- Keras Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf

10- Deep Learning with Keras Cheat Sheet

https://github.com/rstudio/cheatsheets/raw/master/keras.pdf

11- Visual Guide to Neural Network Infrastructures

http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png

12- Skicit-Learn Python Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf

13- Scikit-learn Cheat Sheet: Choosing the Right Estimator

https://scikit-learn.org/stable/tutorial/machine_learning_map/

14- Tensorflow Cheat Sheet

https://github.com/kailashahirwar/cheatsheets-ai/blob/master/PDFs/Tensorflow.pdf

15- Machine Learning Test Cheat Sheet

https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/

@Machine_learn