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

neuralRank: Searching and ranking ANN-based model repositories

Paper: https://lnkd.in/edxKPBH
#artificialinteligence #research #machineleaning #neuralnetworks

✴️ @AI_Python_EN

https://lnkd.in/edT8m4y #machineleaning
“PyText is a deep-learning based NLP modeling framework built on PyTorch”

For those unfamiliar with the man: Schmidhuber is one of the creators of LSTM. Well worth your time.
https://lnkd.in/dYgXxMm

✴️ @AI_Python_EN

Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation
Researchers: Yuyin Zhou, Zhe Li, Song Bai, Chong Wang, Xinlei Chen, Mei Han, Elliot Fishman, Alan Yuille
Paper: http://ow.ly/IdmR50qiURd
#technology #artificialinteligence #machineleaning #bigdata #machinelearning #deeplearning

✴️ @AI_Python_EN

Weakly Supervised Gaussian Networks for Action Detection
Researchers: Basura Fernando, Cheston Tan Yin Chet, Hakan Bilen
Paper: http://ow.ly/NC0S50qAP7S

#artificialinteligence #machineleaning #bigdata #machinelearning #deeplearning

✴️ @AI_Python_EN

HOW DO YOU KNOW THAT YOU HAVE ENOUGH TRAINING DATA? Check out my MEDIUM post:

https://lnkd.in/eVadKPb
#machineleaning

✴️ @AI_Python_EN

LBS Autoencoder: Self-supervised Fitting of Articulated Meshes to Point Clouds

Paper: http://ow.ly/ga4c50rqgsN

#artificialinteligence #machineleaning #bigdata #machinelearning #deeplearning #technology

✴️ @AI_Python_EN

Interpretable and Generalizable Deep Image Matching with Adaptive Convolutions
Researchers: Shengcai Liao, Ling Shao

Paper: http://ow.ly/5z8j50rqdiJ

#artificialinteligence #machineleaning #bigdata #machinelearning #deeplearning

✴️ @AI_Python_EN

💡💡 K-means Clustering – In-depth Tutorial with Example 💡💡

Credits - Data Flair

Link - https://lnkd.in/eCQUriR

#machineleaning #supervisedlearning #unsupervisedlearning #datascience #data #ai # #technology #deeplearning #artificalintelligence

✴️ @AI_Python_EN

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