📘 :Introduction To Graph Neural Network
#book #Graph
@Machine_learn

Fast and Accurate Neural CRF Constituency Parsing

@Machine_learn

Github: https://github.com/yzhangcs/parser

Paper: https://www.ijcai.org/Proceedings/2020/560

​​(Re)Discovering Protein Structure and Function Through Language Modeling

@Machine_learn

Blog: https://blog.einstein.ai/provis/
Paper: https://arxiv.org/abs/2006.15222
Code: https://github.com/salesforce/provis

#DL #NLU #proteinmodelling #bio #biolearning #insilico

Learn Data Analysis with Python
Lessons in Coding
#book #python

@Machine_learn

Private prediction methods: A systematic study by Facebook Research
➡️@Machine_learn
https://ai.facebook.com/blog/private-prediction-methods-a-systematic-study/

Github: https://github.com/facebookresearch/private_prediction

Paper: https://arxiv.org/pdf/2007.05089.pdf

@ai_machinelearning_big_data

Data Analysis
A Model Comparison Approach to Regression, ANOVA, and Beyond
Third Edition
#book
@Machine_learn

Learning perturbation sets for robust machine learning
➡️@Machine_learn

Git: https://locuslab.github.io/2020-07-20-perturbation/

Code: https://github.com/locuslab/perturbation_learning

Paper: https://arxiv.org/abs/2007.08450

Deep Learning and the Game of Go
#book #Dl
@Machine_learn

TensorFlow 2.3 is now officially released
@Machine_learn

https://blog.tensorflow.org/2020/07/whats-new-in-tensorflow-2-3.html

👶 BabyAI 1.1 ➡️@Machine_learn

BabyAI is a platform used to study the sample efficiency of grounded language acquisitio

Github: https://github.com/mila-iqia/babyai
https://github.com/mila-iqia/babyai

Paper: https://arxiv.org/abs/2007.12770v1

@ai_machinelearning_big_data

نسأل الله أن يتقبل منا ومنكم صالح الأعمال، عيدكم مبارك🤍.
@Raminmousa

PIFuHD: new state of the art high-quality 3D reconstruction of humans from a single image
🌐 github.com/facebookresearch/pifuhd
📝 arxiv.org/abs/2004.00452
📉 @Machine_learn

Applied Machine Learning with Python
#book #ml
Andrea Giussani (2020)
@Machine_learn

Whole-Body Human Pose Estimation in the Wild
@Machine_learn

Github: https://github.com/jin-s13/COCO-WholeBody

Paper: https://arxiv.org/abs/2007.11858v1

Dataset: https://cocodataset.org/#keypoints-2017

AI-based Surveying the Impact of Environmental, Climatic, Economic and Demographic Conditions on the Pandemic Outbreak Rate of COVID-19
May 2020
DOI: 10.13140/RG.2.2.22571.87842/1
License: CC BY-NC-ND 4.0
Project: AI-based Surveying the Impact of Environmental, Climatic, Economic and Demographic Conditions on the Epidemic Outbreak Rate of Covid-19
Ramin MousaMehryar MajdMehryar MajdArsalan Mousazadeh

https://www.researchgate.net/publication/343303838_AI-based_Surveying_the_Impact_of_Environmental_Climatic_Economic_and_Demographic_Conditions_on_the_Pandemic_Outbreak_Rate_of_COVID-19/stats
Ramin:@Raminmousa
Arsalan: @arsalan_m

A survey on generative adversarial networks and their variants methods
#GAN
#paper
#survey
@Machine_learn

Tonic deep reinforcement learning library #Rl
@Machine_learn

https://github.com/fabiopardo/tonic