Top 10 IPython Notebook Tutorials for Data Science and Machine Learning
List mostly for beginners.
Link: https://www.kdnuggets.com/2016/04/top-10-ipython-nb-tutorials.html
#novice #beginner #ipython #jupyter
List mostly for beginners.
Link: https://www.kdnuggets.com/2016/04/top-10-ipython-nb-tutorials.html
#novice #beginner #ipython #jupyter
Tomorrow (05 Jan) we are holding first offline meeting for this channel members and all the Data Scientists in Paris.
You are kindly welcome to come by Malongo cafΓ© at 10:00 to chat, share experience and have a coffee with fellow data scientist if you are in Paris these days.
You are kindly welcome to come by Malongo cafΓ© at 10:00 to chat, share experience and have a coffee with fellow data scientist if you are in Paris these days.
A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain
Computer Vision can detect Alzheimerβs Disease in brain scans SIX YEARS before a diagnosis. Uses PET scans, which are common & cheaper. 82% specificity at 100% sensitivity. Can pick out signs hard to see with the naked eye.
Link: https://pubs.rsna.org/doi/10.1148/radiol.2018180958
#CV #DL #Alzheimer #medical
Computer Vision can detect Alzheimerβs Disease in brain scans SIX YEARS before a diagnosis. Uses PET scans, which are common & cheaper. 82% specificity at 100% sensitivity. Can pick out signs hard to see with the naked eye.
Link: https://pubs.rsna.org/doi/10.1148/radiol.2018180958
#CV #DL #Alzheimer #medical
ββAutomatically Generating Comments for Arbitrary Source Code
Automatically generating code comments directly from source code using an LSTM. Works with multiple languages. Canβt wait to JetBrains discovering it.
Link: https://www.twosixlabs.com/automatically-generating-comments-for-arbitrary-source-code/
#NLP #CS #coding #LSTM
Automatically generating code comments directly from source code using an LSTM. Works with multiple languages. Canβt wait to JetBrains discovering it.
Link: https://www.twosixlabs.com/automatically-generating-comments-for-arbitrary-source-code/
#NLP #CS #coding #LSTM
ββGeneralization in Deep Networks: The Role of Distance from Initialization
Why it's important to take into account the initialization to explain generalization.
ArXiV: https://arxiv.org/abs/1901.01672
#DL #NN
Why it's important to take into account the initialization to explain generalization.
ArXiV: https://arxiv.org/abs/1901.01672
#DL #NN
ββReproducibility tool for #Jupyter Notebooks
Link: https://mybinder.org
#DS #github #reproducibleresearch
Link: https://mybinder.org
#DS #github #reproducibleresearch
ββPOET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the Paired Open-Ended Trailblazer
POET: it generates its own increasingly complex, diverse training environments & solves them. It automatically creates a learning curricula & training data, & potentially innovates endlessly.
Link: https://eng.uber.com/poet-open-ended-deep-learning/
#RL #Uber
POET: it generates its own increasingly complex, diverse training environments & solves them. It automatically creates a learning curricula & training data, & potentially innovates endlessly.
Link: https://eng.uber.com/poet-open-ended-deep-learning/
#RL #Uber
YouTube
POET: Endlessly Generating Increasingly Complex & Diverse Learning Environments and their Solutions
This video introduces an algorithm called POET (Paired Open-Ended Trailblazer) that is designed to continually invent increasingly complex and diverse problems, along with their corresponding solutions. Here, we demonstrate POET's potential by unleashingβ¦
ββSuper-resolution GANs for improving the texture resolution of old games.
It is what it is. #GAN to enhance textures in old games making them look better.
ArXiV: https://arxiv.org/abs/1809.00219
Link: https://www.gamespot.com/forums/pc-mac-linux-society-1000004/esrgan-is-pretty-damn-amazing-trying-max-payne-wit-33449670/
#gaming #superresolution
It is what it is. #GAN to enhance textures in old games making them look better.
ArXiV: https://arxiv.org/abs/1809.00219
Link: https://www.gamespot.com/forums/pc-mac-linux-society-1000004/esrgan-is-pretty-damn-amazing-trying-max-payne-wit-33449670/
#gaming #superresolution
Scikit-learn drops support of Python2.7 with new PR.
It means scikit-learn master now requires Python >= 3.5.
https://github.com/scikit-learn/scikit-learn/pull/12639
#scikitlearn
It means scikit-learn master now requires Python >= 3.5.
https://github.com/scikit-learn/scikit-learn/pull/12639
#scikitlearn
GitHub
MRG Drop legacy python / remove six dependencies by amueller Β· Pull Request #12639 Β· scikit-learn/scikit-learn
Tries to drop legacy python (2.7) and remove six everywhere.
ββDeepTraffic β new RL competition hosted by #MIT
Link: https://selfdrivingcars.mit.edu/deeptraffic/
Github: https://github.com/lexfridman/deeptraffic
#RL #selfdrivingcar
Link: https://selfdrivingcars.mit.edu/deeptraffic/
Github: https://github.com/lexfridman/deeptraffic
#RL #selfdrivingcar
A visual exploration of Gaussian Processes: beautiful interactive plots and a brief tutorial to make GPs more approachable
Link: https://www.jgoertler.com/visual-exploration-gaussian-processes/
#Statistics #GP #GaussianProcesses
Link: https://www.jgoertler.com/visual-exploration-gaussian-processes/
#Statistics #GP #GaussianProcesses
Jochen GΓΆrtler
A Visual Exploration of Gaussian Processes
How to turn a collection of small building blocks into a versatile tool for solving regression problems.
Evaluating gambles using dynamics
Link: https://aip.scitation.org/doi/10.1063/1.4940236
#Statistics #Gambling
Link: https://aip.scitation.org/doi/10.1063/1.4940236
#Statistics #Gambling
AIP Publishing
Evaluating gambles using dynamics
Gambles are random variables that model possible changes in wealth. Classic decision theory transforms money into utility through a utility function and defines
ββHow Uber predicts prices
Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber
Link: https://eng.uber.com/neural-networks-uncertainty-estimation/
#RNN #LSTM #Uber
Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber
Link: https://eng.uber.com/neural-networks-uncertainty-estimation/
#RNN #LSTM #Uber
Plug-and-play differential privacy for your tensorflow code
#GoogleAI has just released a new library for training machine learning models with (differential) privacy for training data.
where you would write
instead just swap in the
Tutorial: https://github.com/tensorflow/privacy/blob/master/tutorials/mnist_dpsgd_tutorial.py
Link: https://github.com/tensorflow/privacy
#Privacy #tensorflow
#GoogleAI has just released a new library for training machine learning models with (differential) privacy for training data.
where you would write
tf.train.GradientDescentOptimizer
instead just swap in the
DPGradientDescentOptimizer
Tutorial: https://github.com/tensorflow/privacy/blob/master/tutorials/mnist_dpsgd_tutorial.py
Link: https://github.com/tensorflow/privacy
#Privacy #tensorflow
GitHub
privacy/tutorials/mnist_dpsgd_tutorial.py at master Β· tensorflow/privacy
Library for training machine learning models with privacy for training data - tensorflow/privacy
ββDesnapify
Logical followup of #pix2pix project by Isola et al., based on on Keras implementation by Thibault de Boissiere allows to remove that kat/dog faces from #Snapchat photoes.
Github: https://github.com/ipsingh06/ml-desnapify
Mentioned #Keras repo: https://github.com/tdeboissiere/DeepLearningImplementations/tree/master/pix2pix
#DL
Logical followup of #pix2pix project by Isola et al., based on on Keras implementation by Thibault de Boissiere allows to remove that kat/dog faces from #Snapchat photoes.
Github: https://github.com/ipsingh06/ml-desnapify
Mentioned #Keras repo: https://github.com/tdeboissiere/DeepLearningImplementations/tree/master/pix2pix
#DL