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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
How to use TensorFlow Hub with code examples?
https://medium.com/ymedialabs-innovation/how-to-use-tensorflow-hub-with-code-examples-9100edec29af
#TensorFlow #ArtificialIntelligence
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
https://medium.com/ymedialabs-innovation/how-to-use-tensorflow-hub-with-code-examples-9100edec29af
#TensorFlow #ArtificialIntelligence
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
AI, Python, Cognitive Neuroscience
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…
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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
#opencv #opensourcesoftware #android #computervision #TensorFlow #ArtificialIntelligence #machinelearning
https://medium.com/syncedreview/year-in-review-2018-ai-index-report-out-80880d9241a4
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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.
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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.
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
Excellent presentation by Stanford Graduate School of Business: Blockchain for Social Impact (82 pages)
https://lnkd.in/e6Scvgk #blockchain
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
https://lnkd.in/e6Scvgk #blockchain
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
How to Reduce the Variance of Deep Learning Models in Keras Using Model Averaging Ensembles
#deeplearning #machinelearning
https://bit.ly/2PQlEVu
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
#deeplearning #machinelearning
https://bit.ly/2PQlEVu
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
#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.
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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.
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
https://arxiv.org/abs/1812.08775
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
http://bit.ly/2sSORWi
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
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
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
An Amoeba-Based Computer Calculated Approximate Solutions to a Very Hard Math Problem
Article by Daniel Oberhaus: https://lnkd.in/eHJRTBS
#biocomputers
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
Article by Daniel Oberhaus: https://lnkd.in/eHJRTBS
#biocomputers
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
The Unreasonable Effectiveness of Recurrent Neural Networks
Blog (2015) by Andrej Karpathy: https://lnkd.in/eNC7BK5
#DeepLearning #NeuralNetworks #RecurrentNeuralNetworks #RNN
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
Blog (2015) by Andrej Karpathy: https://lnkd.in/eNC7BK5
#DeepLearning #NeuralNetworks #RecurrentNeuralNetworks #RNN
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
Can Neural Networks Remember?
Slides by Vishal Gupta: https://lnkd.in/e_EUYGv
#RecurrentNeuralNetworks #LongShortTermMemory #LSTM #neuralnetworks
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
Slides by Vishal Gupta: https://lnkd.in/e_EUYGv
#RecurrentNeuralNetworks #LongShortTermMemory #LSTM #neuralnetworks
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
Understanding LSTM Networks
By Christopher Olah: https://lnkd.in/eWJkwp3
#DeepLearning #LSTM #RecurrentNeuralNetworks
❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python
By Christopher Olah: https://lnkd.in/eWJkwp3
#DeepLearning #LSTM #RecurrentNeuralNetworks
❇️ @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
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Wanna see progress of a long running operation easily in your Jupyter notebook? Use the wonderful tqdm module - https://github.com/tqdm/tqdm#ipython-jupyter-integration …. As a bonus, the name is Arabic & Spanish inspired! twitter JupyterProject
Mona Jalal Siad: tqdm stems from تقدم which means "progress"
#python
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
Mona Jalal Siad: tqdm stems from تقدم which means "progress"
#python
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
Eirikur Agustsson Research Scientist Google
this paper on how to properly interpolate samples from GANs and VAEs has been accepted to ICLR 2019!
Paper: Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models (
https://openreview.net/forum?id=BklCusRct7¬eId=BklCusRct7)
TLDR: Stop using linear interpolation!
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
this paper on how to properly interpolate samples from GANs and VAEs has been accepted to ICLR 2019!
Paper: Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models (
https://openreview.net/forum?id=BklCusRct7¬eId=BklCusRct7)
TLDR: Stop using linear interpolation!
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
AI, Python, Cognitive Neuroscience
Wanna see progress of a long running operation easily in your Jupyter notebook? Use the wonderful tqdm module - https://github.com/tqdm/tqdm#ipython-jupyter-integration …. As a bonus, the name is Arabic & Spanish inspired! twitter JupyterProject Mona Jalal…
Could you also consider taking a look at "fastprogress", our recent replacement for tqdm, which has some nice extra features (see the readme) and avoids
some of tqdm's bugs:
https://t.co/QflMyWcUTE
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
some of tqdm's bugs:
https://t.co/QflMyWcUTE
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv