Avoiding Backtesting Overfitting by Covariance-Penalties: an empirical investigation of the ordinary and total least squares cases
Researchers: Adriano Koshiyama, Nick Firoozye
Paper: https://lnkd.in/fWtth8W
#artificialinteligence
#machineleaning #bigdata #machinelearning #deeplearning

✴️ @AI_Python_EN

Use of Artificial Intelligence Techniques / Applications in Cyber Defense
Researcher: Ensar Şeker
Paper: http://ow.ly/eqe450uukBx
#artificialinteligence #machineleaning #bigdata #machinelearning #deeplearning

✴️ @AI_Python_EN

Learning Compositional Neural Programs with Recursive Tree Search and Planning

Paper: http://ow.ly/dEaX50uukqv

#artificialinteligence #machineleaning #bigdata #machinelearning #deeplearning

✴️ @AI_Python_EN

Cracking open the black box of automated machine learning

#MachineLearning
https://bit.ly/2HN9ETC

✴️ @AI_Python_EN

The code for "Learning Undirected Posteriors by Backpropagation through MCMC" is released. I had lots of fun working on this. The paper comes with in-depth discussion of possible future works, ideal for summer interns😉
paper http://bit.ly/2XkcSDJ
code http://bit.ly/2WetVup

✴️ @AI_Python_EN

Bagdasaryan and Shmatikov find that training using private SGD increases error disparities between over and under-represented groups. They blame gradient clipping, which has a larger effect on data points less like the average. An interesting fairness/privacy tradeoff.
Differential Privacy Has Disparate Impact on Model Accuracy.
http://arxiv.org/abs/1905.12101

✴️ @AI_Python_EN

Integrating TVM into PyTorch

https://tvm.ai/2019/05/30/pytorch-frontend

✴️ @AI_Python_EN

How Computers See Introduction to Convolutional Neural Networks

How do self-driving cars read street signs? How does Facebook automatically tag you in pictures? How does a computer achieve

✴️ @AI_Python_EN

Applied Deep Learning for NLP Using PyTorch - PyCon 2019

https://www.youtube.com/watch?v=VBM1u-UIoI0&list=PLPbTDk1hBo3xof51R8pk3kP1BVBuMYP9c&index=1

✴️ @AI_Python_EN

Introduction to Data Science with Python - PyCon 2019

https://www.youtube.com/watch?v=FtaBwrYn-uQ&list=PLPbTDk1hBo3xof51R8pk3kP1BVBuMYP9c&index=7

✴️ @AI_Python_EN

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

https://github.com/RubensZimbres/Repo-2017

✴️ @AI_Python_EN

Natural Language Inference with Deep Learning

Slides for the 2019 NAACL tutorial on Natural Language Inference with Deep Learning by Sam Bowman and Xiaodan Zhu: https://lnkd.in/eRicsNj

#artificialintelligence #deeplearning #naturallanguage

✴️ @AI_Python_EN

Tutorials on NLP from #NAACL2019. Thanks to the authors for sharing them with us to learn.

Deep Adversarial Learning for NLP - https://lnkd.in/fS9rCEv
Natural Language Inference with Deep Learning - https://lnkd.in/fk6MZea
Transfer Learning in NLP - https://lnkd.in/f6S8R6S

✴️ @AI_Python_EN

3DPalsyNet: A Facial Palsy Grading and Motion Recognition Framework using Fully 3D Convolutional Neural Networks
Researchers: Gary Storey, Richard Jiang, Shelagh Keogh, Ahmed Bouridane, Chang-Tsun Li
Paper: http://ow.ly/9aMK50uuW68
#artificialinteligence #machineleaning #bigdata #machinelearning #deeplearning

✴️ @AI_Python_EN

Empowering you to use machine learning to get valuable insights from data.

🔥 Implement basic ML algorithms and deep neural networks with PyTorch.
🖥 Run everything on the browser without any set up using Google Colab.
📦 Learn object-oriented ML to code for products, not just tutorials.

Github Link - https://lnkd.in/f8nu8UR

#datascience #data #dataanalysis #ml #machinelearning #deeplearning #ai #artificialintelligence

✴️ @AI_Python_EN

Sketch2code: Generating a website from a paper mockup
Researcher: Alex Robinson
Paper: http://ow.ly/zXHK50uuW3g
#artificialinteligence #machineleaning #bigdata #machinelearning #deeplearning
✴️ @AI_Python_EN

Roborace is the first racing competition for both autonomous and manual cars. The cars are all electric and have the same power specifications. Teams compete in developing the AI software.

They recently held an event in Spain:
https://lnkd.in/eDTAz8H

Roborace official site:
https://roborace.com/

#ArtificialIntelligence #MachineLearning #ComputerVision

✴️ @AI_Python_EN

EfficientNets: a family of more efficient & accurate image classification models. Found by architecture search and scaled up by one weird trick. Link: https://arxiv.org/abs/1905.11946 Github: https://bit.ly/30UojnC Blog: https://bit.ly/2JKY3qt

On the Fairness of Disentangled Representations

Locatello et al.: https://lnkd.in/d6DV-gX

#ArtificialIntelligence #DeepLearning #MachineLearning

✴️ @AI_Python_EN

FREE Online Classes to learn Data Science, Blockchain, Big Data :

Just choose your learning path, finish the courses and put the #Badge in your LinkedIn profile to attract more recruiters!

✅The learning path:
https://lnkd.in/gKTnANk

💡List of some the courses:
1)Introduction to Data Science
https://lnkd.in/fF79bEj
2)Data Science Tools
https://lnkd.in/fYf2ZC8
3)Data Science Methodology
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4)Statistics
https://lnkd.in/fpgJf7D
5)Predictive Modeling Fundamentals I
https://lnkd.in/f9_Y7UZ
6)Python for Data Science
https://lnkd.in/fy8E2wH
7)Data Analysis with Python
https://lnkd.in/fRQWByd
8)Data Visualization with Python
https://lnkd.in/fFu93ME
9)Machine Learning with Python
https://lnkd.in/f_7r534
10)Deep Learning Fundamentals
https://lnkd.in/fNvPvix
11)Deep Learning with TensorFlow
https://lnkd.in/ftfRtvQ
and many more...

📚Don't miss top 5 free essential books for Data scientists:
https://lnkd.in/gKYqpfV

#datascience #deeplearning #python #machinelearning #ai #hadoop #bigdata #scala #kubernetes #blockchain

✴️ @AI_Python_EN

Notes from Karpathy on common mistakes when training NN
http://karpathy.github.io/2019/04/25/recipe/

✴️ @AI_Python_EN