here are several machine learning algorithms industry has in place.

Here is a simple #MachineLearning #Algorithm Matrix organized by Type, Class, Restriction Bias and Preference Bias.

#artificialintelligence #matrix #deeplearning

Source: https://lnkd.in/dHGCjh8

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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

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Super cool news from Zalando Research. The new version 0.4 of flair, a very simple framework for state-of-the-art NLP, includes BERT, ELMo, Flair word embeddings and also many pre-trained multilingual models. Now it's even easier to do named entity recognition, part-of-speech tagging etc with state of the art models. Check it out!
#deeplearning #machinelearning #NLP

Github: https://lnkd.in/d5B42ac


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Happy Yalda Night 🍉 🤗

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Library for training machine learning models with privacy for training data

TensorFlow Privacy: https://lnkd.in/e4VxTPw

#machinelearning #privacy #tensorflow

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Many problems in physical and biological sciences as well as engineering rely on our ability to monitor objects or processes at nano-scale, and fluorescence microscopy has been used for decades as one of our most useful information sources, leading to various discoveries about the inner workings of nano-scale processes, for example at the sub-cellular level. Imaging of such nano-scale objects often requires rather expensive and delicate instrumentation, also known as nanoscopy tools, which can only be accessed by professionals in well-resourced labs.

The technique transforms low-resolution images from a fluorescence microscope
(a) into super-resolution images
(b) that compare favorably with those from high-resolution equipment
(c). Images show sub-cellular proteins within a cell, and different panels correspond to different observation times.
https://lnkd.in/drbW2P2

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Open sourcing wav2letter++, the fastest state-of-the-art speech system, and flashlight, an ML library going native

By Facebook Artificial Intelligence Research (FAIR): https://lnkd.in/edf6qkV

#ArtificialIntelligence #Research

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OpenCV on Android = Compact size and Optimized (pick the modules that matters to you), build your own SDK for Android.

If you choose OpenCV for production, your primary goal is to bring down the size of the library and also make it performance packed. OpenCV is an awesome library with tons of algorithms but you must be using a very small subset of these algorithm in your application, hence it makes perfect sense to include what is required and leave out the rest.

#opencv #opensourcesoftware #android #computervision

https://medium.com/@tomdeore/opencv-on-android-tiny-with-optimization-enabled-932460acfe38

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How to use TensorFlow Hub with code examples?

https://medium.com/ymedialabs-innovation/how-to-use-tensorflow-hub-with-code-examples-9100edec29af

#TensorFlow #ArtificialIntelligence

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Year-in-Review: 2018 AI Index Report Out! – SyncedReview – Medium

#opencv #opensourcesoftware #android #computervision #TensorFlow #ArtificialIntelligence #machinelearning

https://medium.com/syncedreview/year-in-review-2018-ai-index-report-out-80880d9241a4

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🗒Towards Visible and Thermal Drone Monitoring with Convolutional Neural Networks.
📗PDF

#arXiv
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The #TorontoAI group is viewing (from home) the recent #DeepMind lecture series on #deeplearning - the first video of the series is today at 7:30pm EST.

Here's what we do: Each Wednesday, we start the video at the very same moment, and then that is followed by open community discussion.



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Excellent presentation by Stanford Graduate School of Business: Blockchain for Social Impact (82 pages)
https://lnkd.in/e6Scvgk #blockchain

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How to Reduce the Variance of Deep Learning Models in Keras Using Model Averaging Ensembles

#deeplearning #machinelearning

https://bit.ly/2PQlEVu


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#Statistics don't lie, but statisticians may
Data Science isn't tough, but Data Scientists should be.

#datascience #aspirants tell me the hurdles you are facing every day in your transition. I would like to hear out. I have a lot of friends in my network who can answer. Even I will.

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Amazing. Train a network to classify papers (accept/reject). Then run the network on the paper describing the network, and it classifies the paper as a strong reject. This is why we can't have nice paper classifiers.

https://arxiv.org/abs/1812.08775


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Names for collections of code in various languages:

A pile of JavaScript

A crystal of Haskell

An undefinedness of C++

A liability of Python

A French grad student of OCaml

An ambition of Rust

A bank of COBOL

A postmodernism of Perl

An accident of C

A Unabomber of Forth

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9,216 IBM Power9 CPUs and 27,648 Nvidia Volta GPUs #Supercomputer performs 200 quadrillion calculations per second, #USA tops #China for the world's fastest #computer #AI #DataScience #DataAnalytics #IoT #BigData

http://bit.ly/2sSORWi

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The FEYNMAN technique of learning:

STEP 1 - Pick and study a topic

STEP 2 - Explain the topic to someone, like a child, who is unfamiliar with the topic

STEP 3 - Identify any gaps in your understanding

STEP 4 - Review and Simplify!

- Richard Feynman

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An Amoeba-Based Computer Calculated Approximate Solutions to a Very Hard Math Problem

Article by Daniel Oberhaus: https://lnkd.in/eHJRTBS

#biocomputers


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The Unreasonable Effectiveness of Recurrent Neural Networks

Blog (2015) by Andrej Karpathy: https://lnkd.in/eNC7BK5

#DeepLearning #NeuralNetworks #RecurrentNeuralNetworks #RNN


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