πΉHow to Build Your Own Deep Learning Box
Want to build an affordable deep learning box and get all the required software installed? Read on for a proper overview.
Credit: By Hui Han Chin, DSO National Laboratories, Singapore.
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πVia: @cedeeplearning
https://www.kdnuggets.com/2016/06/build-deep-learning-box.html
Want to build an affordable deep learning box and get all the required software installed? Read on for a proper overview.
Credit: By Hui Han Chin, DSO National Laboratories, Singapore.
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πVia: @cedeeplearning
https://www.kdnuggets.com/2016/06/build-deep-learning-box.html
KDnuggets
How to Build Your Own Deep Learning Box - KDnuggets
Want to build an affordable deep learning box and get all the required software installed? Read on for a proper overview.
π§ Nanotronics Brings Deep Learning to Precision Manufacturing - Ep. 109
(Podcast)
Matthew Putman, Ep.109βs guest on the AI Podcast, knows that the devil is in the details. Thatβs why heβs the co-founder and CEO of Nanotronics, a Brooklyn-based company providing precision manufacturing enhanced by AI, automation and 3D imaging.
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πVia: @cedeeplearning
https://soundcloud.com/theaipodcast/ai-nanotronics-matthew-putman-3
(Podcast)
Matthew Putman, Ep.109βs guest on the AI Podcast, knows that the devil is in the details. Thatβs why heβs the co-founder and CEO of Nanotronics, a Brooklyn-based company providing precision manufacturing enhanced by AI, automation and 3D imaging.
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πVia: @cedeeplearning
https://soundcloud.com/theaipodcast/ai-nanotronics-matthew-putman-3
SoundCloud
Ep. 109
Matthew Putman, this weekβs guest on the AI Podcast, knows that the devil is in the details. Thatβs why heβs the co-founder and CEO of Nanotronics, a Brooklyn-based company providing precision manufac
π»More Performance Evaluation Metrics for Classification Problems You Should Know
When building and optimizing your classification model, measuring how accurately it predicts your expected outcome is crucial. However, this metric alone is never the entire story, as it can still offer misleading results. That's where these additional performance evaluations come into play to help tease out more meaning from your model.
Credit: By Clare Liu
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πVia: @cedeeplearning
https://www.kdnuggets.com/2020/04/performance-evaluation-metrics-classification.html
#machinelearning
#classification
#recall
#precision
When building and optimizing your classification model, measuring how accurately it predicts your expected outcome is crucial. However, this metric alone is never the entire story, as it can still offer misleading results. That's where these additional performance evaluations come into play to help tease out more meaning from your model.
Credit: By Clare Liu
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πVia: @cedeeplearning
https://www.kdnuggets.com/2020/04/performance-evaluation-metrics-classification.html
#machinelearning
#classification
#recall
#precision
KDnuggets
More Performance Evaluation Metrics for Classification Problems You Should Know
When building and optimizing your classification model, measuring how accurately it predicts your expected outcome is crucial. However, this metric alone is never the entire story, as it can still offer misleading results. That's where these additional performanceβ¦
Perform cross-modal translation from "in-the-wild'' monologue speech of a single speaker to their hand and arm motion.
The project website with video, code and data can be found at http://people.eecs.berkeley.edu/~shiry/speech2gesture.
* CVPR 2019
β Via: @cedeeplearning
β Other social media handles: https://linktr.ee/cedeeplearning
The project website with video, code and data can be found at http://people.eecs.berkeley.edu/~shiry/speech2gesture.
* CVPR 2019
β Via: @cedeeplearning
β Other social media handles: https://linktr.ee/cedeeplearning
Linktree
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Pixel RNN sequentially predicts the pixels in an image along the two spatial dimensions. The method models the discrete probability of the raw pixel values and encodes the complete set of dependencies in the image.
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Paper: https://arxiv.org/abs/1601.06759
Via: @CEdeeplearning π
Other social media: https://linktr.ee/cedeeplearning
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#pixelrnn #generativemodel #computervision #rnn #cnn #neuralnetworks #deeplearning #machinelearning
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Paper: https://arxiv.org/abs/1601.06759
Via: @CEdeeplearning π
Other social media: https://linktr.ee/cedeeplearning
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#pixelrnn #generativemodel #computervision #rnn #cnn #neuralnetworks #deeplearning #machinelearning
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πΉUsing machine learning to analyze whole brain vasculature
Source: Helmholtz Zentrum MΓΌnchen
Diseases of the brain are often associated with typical vascular changes. Now, scientists at Helmholtz Zentrum MΓΌnchen, LMU University Hospital Munich and the Technical University of Munich have come up with a technique for visualizing the structures of all the brainβs blood vessels β right down to the finest capillaries β including any pathological changes. So far, they have used the technique, which is based on a combination of biochemical methods and artificial intelligence, to capture the whole brain vasculature of a mouse.
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πVia: @cedeeplearning
https://neurosciencenews.com/machine-learning-brain-vasculature-15909/
#machinelearning
#deeplearning
#neuralnetworks
Source: Helmholtz Zentrum MΓΌnchen
Diseases of the brain are often associated with typical vascular changes. Now, scientists at Helmholtz Zentrum MΓΌnchen, LMU University Hospital Munich and the Technical University of Munich have come up with a technique for visualizing the structures of all the brainβs blood vessels β right down to the finest capillaries β including any pathological changes. So far, they have used the technique, which is based on a combination of biochemical methods and artificial intelligence, to capture the whole brain vasculature of a mouse.
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πVia: @cedeeplearning
https://neurosciencenews.com/machine-learning-brain-vasculature-15909/
#machinelearning
#deeplearning
#neuralnetworks
Neuroscience News
Using machine learning to analyze whole brain vasculature - Neuroscience News
Combining advance microscopy techniques and artificial intelligence, researchers reconstruct the entire vascular network of a mouse brain down to its finest details.
π»New study allows brain and artificial neurons to link up over the web
Source: University of Southampton
Researchers have created a hybrid neural network where biological and artificial neurons in different parts of the world were able to communicate via the internet through a hub of memristive synapses.
Brain functions are made possible by circuits of spiking neurons, connected together by microscopic, but highly complex links called βsynapsesβ. In this new study, published in the scientific journal Nature Scientific Reports, the scientists created a hybrid neural network where biological and artificial neurons in different parts of the world were able to communicate with each other over the internet through a hub of artificial synapses made using cutting-edge nanotechnology. This is the first time the three components have come together in a unified network.
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
#machinelearning
#neuralnetworks
#deeplearning
#AI
Source: University of Southampton
Researchers have created a hybrid neural network where biological and artificial neurons in different parts of the world were able to communicate via the internet through a hub of memristive synapses.
Brain functions are made possible by circuits of spiking neurons, connected together by microscopic, but highly complex links called βsynapsesβ. In this new study, published in the scientific journal Nature Scientific Reports, the scientists created a hybrid neural network where biological and artificial neurons in different parts of the world were able to communicate with each other over the internet through a hub of artificial synapses made using cutting-edge nanotechnology. This is the first time the three components have come together in a unified network.
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
#machinelearning
#neuralnetworks
#deeplearning
#AI
Linktree
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π»Using computers to view the unseen
From: Rachel Gordon
A new computational imaging method could change how we view hidden information in scenes.
Cameras and computers together can conquer some seriously stunning feats. Giving computers vision has helped us fight wildfires in California, understand complex and treacherous roads β and even see around corners.
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πVia: @cedeeplearning
http://news.mit.edu/2019/using-computers-view-unseen-computational-mirrors-mit-csail-1206
#deeplearning
#computervision
#neuralnetworks
#objectdetection
#machinelearning
From: Rachel Gordon
A new computational imaging method could change how we view hidden information in scenes.
Cameras and computers together can conquer some seriously stunning feats. Giving computers vision has helped us fight wildfires in California, understand complex and treacherous roads β and even see around corners.
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πVia: @cedeeplearning
http://news.mit.edu/2019/using-computers-view-unseen-computational-mirrors-mit-csail-1206
#deeplearning
#computervision
#neuralnetworks
#objectdetection
#machinelearning
MIT News
Using computers to view the unseen
Scientists from MITβs Computer Science and Artificial Intelligence Laboratory (CSAIL) can reconstruct hidden video from just the subtle shadows and reflections on an observed pile of clutter.
ππ»ππ»Using computers to view the unseen
https://youtu.be/hhEJMpouMS8
πVia: @cedeeplearning
https://youtu.be/hhEJMpouMS8
πVia: @cedeeplearning
YouTube
Computational Mirrors: Revealing Hidden Video
Paper: https://arxiv.org/abs/1912.02314
Project page: http://compmirrors.csail.mit.edu/
Project page: http://compmirrors.csail.mit.edu/
πΉWhat a little more #computing_power can do
From: Kim Martineau
To recognize a cat in a picture, a deep learning model may need to see millions of photos before its artificial #neurons βlearnβ to identify a cat. But there may be a more efficient way. New MIT research shows that models only a fraction of the size are needed. βWhen you train a big network thereβs a small one that could have done everything,β. neural network could get by with on-tenth the number of connections if the right subnetwork is found at the outset.
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2019/what-extra-computing-power-can-do-0916
#neuralnetworks
#GAN
#deeplearning
#machinelearning
From: Kim Martineau
To recognize a cat in a picture, a deep learning model may need to see millions of photos before its artificial #neurons βlearnβ to identify a cat. But there may be a more efficient way. New MIT research shows that models only a fraction of the size are needed. βWhen you train a big network thereβs a small one that could have done everything,β. neural network could get by with on-tenth the number of connections if the right subnetwork is found at the outset.
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2019/what-extra-computing-power-can-do-0916
#neuralnetworks
#GAN
#deeplearning
#machinelearning
π»Supercomputer analyzes web traffic across entire internet
From: Rob Matheson
Using a supercomputing system, MIT researchers have developed a model that captures what web traffic looks like around the world on a given day, which can be used as a measurement tool for internet research and many other applications.
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πVia: @cedeeplearning
http://news.mit.edu/2019/supercomputer-analyzes-web-traffic-across-entire-internet-1028
#deeplearning
#neuralnetworks
#supercomputer
#machinelearning
#AI
From: Rob Matheson
Using a supercomputing system, MIT researchers have developed a model that captures what web traffic looks like around the world on a given day, which can be used as a measurement tool for internet research and many other applications.
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πVia: @cedeeplearning
http://news.mit.edu/2019/supercomputer-analyzes-web-traffic-across-entire-internet-1028
#deeplearning
#neuralnetworks
#supercomputer
#machinelearning
#AI
MIT News | Massachusetts Institute of Technology
Supercomputer analyzes web traffic across entire internet
Using the MIT SuperCloud and the MIT Lincoln Laboratory Supercomputing Center, researchers have developed a model that captures what web traffic looks like around the world on a given day, to be used as a measurement tool for internet and network research.
πΉAlgorithms, Libraries, Toolkits and Platformsβ¦
There are a multitude of technologies and frameworks on the market today that enable data scientists and machine learning engineers to build, deploy and maintain machine learning systems, pipelines and workflows. Just like any economic matter, supply and demand drives the improvement and progress of the product. As the use of machine learning in business increases, so does the number of frameworks and software that facilitate full-fledged machine learning workflows.
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
link: https://www.rocketsource.co/blog/machine-learning-models/
#machinelearning
#algorithm
#library
#platform
#technology
There are a multitude of technologies and frameworks on the market today that enable data scientists and machine learning engineers to build, deploy and maintain machine learning systems, pipelines and workflows. Just like any economic matter, supply and demand drives the improvement and progress of the product. As the use of machine learning in business increases, so does the number of frameworks and software that facilitate full-fledged machine learning workflows.
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
link: https://www.rocketsource.co/blog/machine-learning-models/
#machinelearning
#algorithm
#library
#platform
#technology
πΉNew Visual Relationships, Human Actions, and Image-Level Annotations
Open Images V6 is a significant qualitative and quantitative step towards improving the unified annotations for image classification, object detection, visual relationship detection, and instance segmentation, and takes a novel approach in connecting vision and language with localized narratives. We hope that Open Images V6 will further stimulate progress towards genuine scene understanding.
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
Credit: ai.googleblog.com
#classification
#machinelearning
#deeplearning
#imagedetection
Open Images V6 is a significant qualitative and quantitative step towards improving the unified annotations for image classification, object detection, visual relationship detection, and instance segmentation, and takes a novel approach in connecting vision and language with localized narratives. We hope that Open Images V6 will further stimulate progress towards genuine scene understanding.
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
Credit: ai.googleblog.com
#classification
#machinelearning
#deeplearning
#imagedetection
πΉPhoto Editing with Generative Adversarial Networks
#GANs are a very hot topic in #Machine_Learning. In this post I will explore various ways of using a GAN to create previously unseen images. I provide source code in #Tensorflow and a modified version of DIGITS that you are free to use if you wish to try it out yourself.
π»Do not miss out this article
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
link: https://devblogs.nvidia.com/photo-editing-generative-adversarial-networks-1/
#GANs are a very hot topic in #Machine_Learning. In this post I will explore various ways of using a GAN to create previously unseen images. I provide source code in #Tensorflow and a modified version of DIGITS that you are free to use if you wish to try it out yourself.
π»Do not miss out this article
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
link: https://devblogs.nvidia.com/photo-editing-generative-adversarial-networks-1/
π»DEPLOYING COMPUTER VISION TO HELP SOCIAL DISTANCING AMID PANDEMIC OUTBREAK
This can help to:
Β· Know the number of people in given public place or facility
Β· If the gatherings are confined by mandated congregation limit
Β· Know where and when the cleaning personnel should focus their activities of sanitizing and waste disposal
Β· Check if people are wearing face masks in the suggested regions
Β· Observe if people are following recommended social distancing policies.
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πVia: @cedeeplearning
https://www.analyticsinsight.net/deploying-computer-vision-to-help-in-social-distancing-amid-pandemic-outbreak/
#computervision
#AI
#COVID19
#deeplearning
#machinelearning
This can help to:
Β· Know the number of people in given public place or facility
Β· If the gatherings are confined by mandated congregation limit
Β· Know where and when the cleaning personnel should focus their activities of sanitizing and waste disposal
Β· Check if people are wearing face masks in the suggested regions
Β· Observe if people are following recommended social distancing policies.
ββββββββββββ
πVia: @cedeeplearning
https://www.analyticsinsight.net/deploying-computer-vision-to-help-in-social-distancing-amid-pandemic-outbreak/
#computervision
#AI
#COVID19
#deeplearning
#machinelearning
Analytics Insight
Deploying Computer Vision to Help Social Distancing Amid Coronavirus Outbreak
Zensors, a Carnegie Mellon University startup enables smart and reactive spaces with better crowd screening through cutting-edge computer vision technologies. This Computer vision activity monitoring startup developed a suite of tools that uses machine learningβ¦
πΉBENEFITS OF SPARK NLP
1. Itβs very accurate
2. Reduced training model sizes
3. Itβs fast
4. It is fully supported by Spark
5. It is scalable
6. Extensive functionality and support
7. A large community
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
link: https://www.analyticsinsight.net/benefits-of-spark-nlp/
#spark
#NLP
#deeplearning
#neuralnetworks
1. Itβs very accurate
2. Reduced training model sizes
3. Itβs fast
4. It is fully supported by Spark
5. It is scalable
6. Extensive functionality and support
7. A large community
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πVia: @cedeeplearning
πSocial media: https://linktr.ee/cedeeplearning
link: https://www.analyticsinsight.net/benefits-of-spark-nlp/
#spark
#NLP
#deeplearning
#neuralnetworks