"Training Neural Nets on Larger Batches: Practical Tips for 1-GPU, Multi-GPU & Distributed setups"
By Thomas Wolf: https://lnkd.in/etyMzjQ
#ArtificialInteligence #DeepLearning #MachineLearning #NeuralNetworks
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
By Thomas Wolf: https://lnkd.in/etyMzjQ
#ArtificialInteligence #DeepLearning #MachineLearning #NeuralNetworks
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
A simple notebook to remove the background of objects using Mask R-CNN
By Zaid Alyafeai: https://lnkd.in/exr7yWi
#artificialinteligence #deeplearning #machinelearning #tensorflow
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_Arxiv
By Zaid Alyafeai: https://lnkd.in/exr7yWi
#artificialinteligence #deeplearning #machinelearning #tensorflow
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_Arxiv
10 Exciting Ideas of 2018 in NLP
A collection of 10 exciting and impactful ideas in 2018, by Sebastian Ruder: https://lnkd.in/ebb2Qix
#artificialinteligence #deeplearning #machinelearning #NLP #unsupervisedlearning
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
A collection of 10 exciting and impactful ideas in 2018, by Sebastian Ruder: https://lnkd.in/ebb2Qix
#artificialinteligence #deeplearning #machinelearning #NLP #unsupervisedlearning
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
Deep Paper Gestalt
"Experimental results show that our classifier can safely reject 50% of the bad papers while wrongly reject only 0.4% of the good papers, and thus dramatically reduce the workload of the reviewers."
GitHub: https://lnkd.in/epwDePX
#artificialinteligence #deeplearning #machinelearning
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
"Experimental results show that our classifier can safely reject 50% of the bad papers while wrongly reject only 0.4% of the good papers, and thus dramatically reduce the workload of the reviewers."
GitHub: https://lnkd.in/epwDePX
#artificialinteligence #deeplearning #machinelearning
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
Best of arXiv.org for AI, Machine Learning, and Deep Learning
🔸 November 2018
🔸 November 2017
🔸 July 2018
🔸 April 2018
🔸 June 2018
🔸 September 2018
🔸 October 2018
🔸 August 2018
#DeepLearning #machinelearning #AI #Artificialinteligence #مقاله
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
🔸 November 2018
🔸 November 2017
🔸 July 2018
🔸 April 2018
🔸 June 2018
🔸 September 2018
🔸 October 2018
🔸 August 2018
#DeepLearning #machinelearning #AI #Artificialinteligence #مقاله
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
DATASET DISTILLATION
Anonymous authors: https://lnkd.in/ekqYXTs
#artificialinteligence #deeplearning #machinelearning
If you like our channel, i invite you to share it with your friends
✴️ @AI_Python_EN
🗣 @AI_Python_Arxiv
Anonymous authors: https://lnkd.in/ekqYXTs
#artificialinteligence #deeplearning #machinelearning
If you like our channel, i invite you to share it with your friends
✴️ @AI_Python_EN
🗣 @AI_Python_Arxiv
The Best #FREE Books for Learning #DataScience
Link => bit.ly/AIFreeBooks
#ai #analytics #artificialinteligence #bi #bigdata #data #machinelearning
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
Link => bit.ly/AIFreeBooks
#ai #analytics #artificialinteligence #bi #bigdata #data #machinelearning
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
WHAT IS USE CASES DATA SCIENCE IN HR?
Data science is not only intended for those who want to become data scientists. Data Science is a science that can be applied to HR as well. Here are some reasons why a recruiter also needs to learn data science:
1. Strategic recruitment by learning data science
https://lnkd.in/f3S8zvA
2. Future recruitment processes are in AI
https://lnkd.in/fqvemej
3. Data Science selection process
https://lnkd.in/fiCRwPW
4. You can become a Recruitment Specialist in data science.
https://lnkd.in/fNGvtpG
5. You can design a dashboard that is ideal for the recruitment process.
https://lnkd.in/fghidHC
6. Insight on learning data science
https://lnkd.in/g5n3bRn
7. Predicting Employe Turover
https://lnkd.in/fkMu3A6
8. AI for Candidate Selection
https://lnkd.in/f7Kf3Mf
9. Increasing Employee Happiness
https://lnkd.in/fTzNbsC
10. Predicting Performance
https://lnkd.in/fdCmR-B
#datascience #humanresource #artificialinteligence #analytics
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
Data science is not only intended for those who want to become data scientists. Data Science is a science that can be applied to HR as well. Here are some reasons why a recruiter also needs to learn data science:
1. Strategic recruitment by learning data science
https://lnkd.in/f3S8zvA
2. Future recruitment processes are in AI
https://lnkd.in/fqvemej
3. Data Science selection process
https://lnkd.in/fiCRwPW
4. You can become a Recruitment Specialist in data science.
https://lnkd.in/fNGvtpG
5. You can design a dashboard that is ideal for the recruitment process.
https://lnkd.in/fghidHC
6. Insight on learning data science
https://lnkd.in/g5n3bRn
7. Predicting Employe Turover
https://lnkd.in/fkMu3A6
8. AI for Candidate Selection
https://lnkd.in/f7Kf3Mf
9. Increasing Employee Happiness
https://lnkd.in/fTzNbsC
10. Predicting Performance
https://lnkd.in/fdCmR-B
#datascience #humanresource #artificialinteligence #analytics
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
MIT : Intro to Deep Learning
First two 2019 lectures for MIT Intro to #DeepLearning now online!
Course schedule: https://lnkd.in/eDW7FTs
Lecture 1: https://lnkd.in/esDcMaP
Lecture 2: https://lnkd.in/epzKtXM
#artificialinteligence #machineleaning #neuralnetworks
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
First two 2019 lectures for MIT Intro to #DeepLearning now online!
Course schedule: https://lnkd.in/eDW7FTs
Lecture 1: https://lnkd.in/esDcMaP
Lecture 2: https://lnkd.in/epzKtXM
#artificialinteligence #machineleaning #neuralnetworks
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
neuralRank: Searching and ranking ANN-based model repositories
Paper: https://lnkd.in/edxKPBH
#artificialinteligence #research #machineleaning #neuralnetworks
✴️ @AI_Python_EN
Paper: https://lnkd.in/edxKPBH
#artificialinteligence #research #machineleaning #neuralnetworks
✴️ @AI_Python_EN