🔹A foolproof way to shrink deep learning models
by Kim Martineau
🔻Researchers unveil a pruning algorithm to make artificial intelligence applications run faster.
As more artificial intelligence applications move to smartphones, deep learning models are getting smaller to allow apps to run faster and save battery power. Now, MIT researchers have a new and better way to compress models. It’s so simple that they unveiled it in a tweet last month: Train the model, prune its weakest connections, retrain the model at its fast, early training rate, and repeat, until the model is as tiny as you want.
🔻Do not miss out this article from MIT News
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📌Via: @cedeeplearning
link: http://news.mit.edu/2020/foolproof-way-shrink-deep-learning-models-0430
#deeplearning #machinelearning
#datascience #math
#AI #neuralnetworks
by Kim Martineau
🔻Researchers unveil a pruning algorithm to make artificial intelligence applications run faster.
As more artificial intelligence applications move to smartphones, deep learning models are getting smaller to allow apps to run faster and save battery power. Now, MIT researchers have a new and better way to compress models. It’s so simple that they unveiled it in a tweet last month: Train the model, prune its weakest connections, retrain the model at its fast, early training rate, and repeat, until the model is as tiny as you want.
🔻Do not miss out this article from MIT News
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📌Via: @cedeeplearning
link: http://news.mit.edu/2020/foolproof-way-shrink-deep-learning-models-0430
#deeplearning #machinelearning
#datascience #math
#AI #neuralnetworks
🔹Jump-start Training for #Speech_Recognition Models in Different Languages with NVIDIA NeMo
🖊By Oleksii Kuchaiev
Transfer learning is an important machine learning technique that uses a model’s knowledge of one task to make it perform better on another. Fine-tuning is one of the techniques to perform transfer learning.
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📌Via: @cedeeplearning
https://devblogs.nvidia.com/jump-start-training-for-speech-recognition-models-with-nemo/
#deeplearning #neuralnetworks
#machinelearning #NVIDIA
#AI #datascience #math
#nemo #model #data
🖊By Oleksii Kuchaiev
Transfer learning is an important machine learning technique that uses a model’s knowledge of one task to make it perform better on another. Fine-tuning is one of the techniques to perform transfer learning.
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📌Via: @cedeeplearning
https://devblogs.nvidia.com/jump-start-training-for-speech-recognition-models-with-nemo/
#deeplearning #neuralnetworks
#machinelearning #NVIDIA
#AI #datascience #math
#nemo #model #data
NVIDIA Developer Blog
Jump-start Training for Speech Recognition Models in Different Languages with NVIDIA NeMo | NVIDIA Developer Blog
Transfer learning is an important machine learning technique that uses a model’s knowledge of one task to make it perform better on another. Fine-tuning is one of the techniques to perform transfer…
🔹Announcing NVIDIA NeMo: Fast Development of Speech and Language Models
🖊By Raghav Mani
🔻The inputs and outputs, coding style, and data processing layers in these models may not be compatible with each other. Worse still, you may be able to wire up these models in your code in such a way that it technically “works” but is in fact semantically wrong. A lot of time, effort, and duplicated code goes into making sure that you are reusing models safely.
🔻Build a simple ASR model to see how to use NeMo. You see how neural types provide semantic safety checks, and how the tool can scale out to multiple GPUs with minimal effort.
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📌Via: @cedeeplearning
https://devblogs.nvidia.com/announcing-nemo-fast-development-of-speech-and-language-models/
#deeplearning #neuralnetworks
#machinelearning #NVIDIA
#AI #datascience #math
#nemo #model #data
🖊By Raghav Mani
🔻The inputs and outputs, coding style, and data processing layers in these models may not be compatible with each other. Worse still, you may be able to wire up these models in your code in such a way that it technically “works” but is in fact semantically wrong. A lot of time, effort, and duplicated code goes into making sure that you are reusing models safely.
🔻Build a simple ASR model to see how to use NeMo. You see how neural types provide semantic safety checks, and how the tool can scale out to multiple GPUs with minimal effort.
———————
📌Via: @cedeeplearning
https://devblogs.nvidia.com/announcing-nemo-fast-development-of-speech-and-language-models/
#deeplearning #neuralnetworks
#machinelearning #NVIDIA
#AI #datascience #math
#nemo #model #data
NVIDIA Developer Blog
Announcing NVIDIA NeMo: Fast Development of Speech and Language Models | NVIDIA Developer Blog
As a researcher building state-of-the-art speech and language models, you must be able to quickly experiment with novel network architectures. This experimentation may focus on modifying existing…
📕 State of Deep Reinforcement Learning: Inferring future outlook
Today machines can teach themselves based upon the results of their own actions. This advancement in Artificial Intelligence seems like a promising technology through which we can explore more innovative potentials of AI. The process is termed as deep reinforcement learning.
🔻What Future Holds for Deep Reinforcement Learning?
Experts believe that deep reinforcement learning is at the cutting-edge right now and it has finally reached a to be applied in real-world applications. They also believe that moving it will have a great impact on AI advancement and can eventually researchers closer to Artificial General Intelligence (AGI).
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📌Via: @cedeeplearning
https://www.analyticsinsight.net/state-deep-reinforcement-learning-inferring-future-outlook/
#deeplearning #AI #AGI
#reinforcement #math
#datascience #machinelearning
Today machines can teach themselves based upon the results of their own actions. This advancement in Artificial Intelligence seems like a promising technology through which we can explore more innovative potentials of AI. The process is termed as deep reinforcement learning.
🔻What Future Holds for Deep Reinforcement Learning?
Experts believe that deep reinforcement learning is at the cutting-edge right now and it has finally reached a to be applied in real-world applications. They also believe that moving it will have a great impact on AI advancement and can eventually researchers closer to Artificial General Intelligence (AGI).
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📌Via: @cedeeplearning
https://www.analyticsinsight.net/state-deep-reinforcement-learning-inferring-future-outlook/
#deeplearning #AI #AGI
#reinforcement #math
#datascience #machinelearning
www.analyticsinsight.net
State of Deep Reinforcement Learning: Inferring Future Outlook
Deep reinforcement learning, is a category of machine learning and artificial intelligence, which is advancing at a great pace. Experts believe that its potential advancements to define the future of deep learning can lead to attaining Artificial General…
⭕️ Top 6 Open Source Pre-trained Models for Text Classification you should use
1. XLNet
2. ERNIE
3. Text-to-Text Transfer Transformer (T5)
4. Binary - Partitioning Transformation (BPT)
5. Neural Attentive Bag-of-Entities Model for Text Classification (NABoE)
6. Rethinking Complex Neural Network Architectures for Document Classification
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📌Via: @cedeeplearning
https://www.analyticsvidhya.com/blog/2020/03/6-pretrained-models-text-classification/
#classification #machinelearning
#datascience #model #training
#deeplearning #dataset #neuralnetworks
#NLP #math #AI
1. XLNet
2. ERNIE
3. Text-to-Text Transfer Transformer (T5)
4. Binary - Partitioning Transformation (BPT)
5. Neural Attentive Bag-of-Entities Model for Text Classification (NABoE)
6. Rethinking Complex Neural Network Architectures for Document Classification
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📌Via: @cedeeplearning
https://www.analyticsvidhya.com/blog/2020/03/6-pretrained-models-text-classification/
#classification #machinelearning
#datascience #model #training
#deeplearning #dataset #neuralnetworks
#NLP #math #AI
Analytics Vidhya
Top 6 Open Source Pretrained Models for Text Classification you should use
Pretrained models and transfer learning is used for text classification. Here are the top pretrained models you shold use for text classification.
🔖 The Best NLP with Deep Learning Course is Free
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html
#deeplearning #NLP
#neuralnetworks
#machinelearning
#free #AI #math
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html
#deeplearning #NLP
#neuralnetworks
#machinelearning
#free #AI #math
KDnuggets
The Best NLP with Deep Learning Course is Free - KDnuggets
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
🔻 Deep learning accurately stains digital biopsy slides
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
🔹 This process of computational digital staining and de-staining preserves small amounts of tissue biopsied from cancer patients and allows researchers and clinicians to analyze slides for multiple kinds of diagnostic and prognostic tests, without needing to extract additional tissue sections.
A Good Read 👌
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📌Via: @cedeeplearning
http://news.mit.edu/2020/deep-learning-provides-accurate-staining-digital-biopsy-slides-0522
#deeplearning #machinelearning
#neuralnetworks
#MIT #math #AI
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
🔹 This process of computational digital staining and de-staining preserves small amounts of tissue biopsied from cancer patients and allows researchers and clinicians to analyze slides for multiple kinds of diagnostic and prognostic tests, without needing to extract additional tissue sections.
A Good Read 👌
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📌Via: @cedeeplearning
http://news.mit.edu/2020/deep-learning-provides-accurate-staining-digital-biopsy-slides-0522
#deeplearning #machinelearning
#neuralnetworks
#MIT #math #AI
MIT News
Deep learning accurately stains digital biopsy slides
Digital scans of biopsy slides can be stained computationally, using deep learning algorithms trained on data from physically dyed slides, according to a research team led by MIT scientists at the Media Lab.
⚪️ Visualizing the world beyond the frame
🔹Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.
🔹To give computer vision models a fuller, more imaginative view of the world, researchers have tried feeding them more varied images. Some have tried shooting objects from odd angles, and in unusual positions, to better convey their real-world complexity. Others have asked the models to generate pictures of their own, using a form of artificial intelligence called GANs, or generative adversarial networks. In both cases, the aim is to fill in the gaps of image datasets to better reflect the three-dimensional world and make face- and object-recognition models less biased.
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2020/visualizing-the-world-beyond-the-frame-0506
#deeplearning #GANs #math
#machinelearning #visualization
#AI #MIT #datascience
🔹Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.
🔹To give computer vision models a fuller, more imaginative view of the world, researchers have tried feeding them more varied images. Some have tried shooting objects from odd angles, and in unusual positions, to better convey their real-world complexity. Others have asked the models to generate pictures of their own, using a form of artificial intelligence called GANs, or generative adversarial networks. In both cases, the aim is to fill in the gaps of image datasets to better reflect the three-dimensional world and make face- and object-recognition models less biased.
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2020/visualizing-the-world-beyond-the-frame-0506
#deeplearning #GANs #math
#machinelearning #visualization
#AI #MIT #datascience
❌ Deep learning is a blessing to police for crime investigations
Deep learning architectures these days are applied to computer vision, speech recognition, machine translation, bioinformatics, drug design, crime inspections and various other fields. Deep learning uses deep neural networks based on which actions are triggered and have produced results comparable to human experts. When compared to traditional machine learning algorithms which are linear, deep learning algorithms are hierarchical. These are based on increasing complexity and abstraction. Now, these are helpful in police investigations in the way these processes available information.
In the police investigations, deep learning helps through the video analysis. Videos gathered from multiple sources are feed into the deep learning systems. Through the software, we can identify and differentiate various targets appearing on the footage.
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📌 Via: @cedeeplearning
https://www.analyticsinsight.net/deep-learning-is-a-blessing-to-police-for-investigations/
#deeplearning #machinelearning
#neuralnetworks #videodetection
#analysis #AI #math #datascience
#artificial_intelligence
Deep learning architectures these days are applied to computer vision, speech recognition, machine translation, bioinformatics, drug design, crime inspections and various other fields. Deep learning uses deep neural networks based on which actions are triggered and have produced results comparable to human experts. When compared to traditional machine learning algorithms which are linear, deep learning algorithms are hierarchical. These are based on increasing complexity and abstraction. Now, these are helpful in police investigations in the way these processes available information.
In the police investigations, deep learning helps through the video analysis. Videos gathered from multiple sources are feed into the deep learning systems. Through the software, we can identify and differentiate various targets appearing on the footage.
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📌 Via: @cedeeplearning
https://www.analyticsinsight.net/deep-learning-is-a-blessing-to-police-for-investigations/
#deeplearning #machinelearning
#neuralnetworks #videodetection
#analysis #AI #math #datascience
#artificial_intelligence
www.analyticsinsight.net
Deep Learning Is a Blessing to Police for Crime Investigations |
Deep learning has penetrated deep into the system which can be more helpful in crime investigation and analysis for police. Deep learning differs from artificial intelligence and is a part of a broader family of machine learning.
🔹 How to Think Like a Data Scientist
🖊By Jo Stichbury
🔻So what does it take to become a data scientist? For some pointers on the skills for success, I interviewed Ben Chu, who is a Senior Data Scientist at Refinitiv Labs.
🔻Be curious
🔻Be scientific
🔻Be creative
🔻Learn how to code
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/think-like-data-scientist-data-analyst.html
#datascience #machinelearning
#tutorial #roadmap
#python #math #statistics #neuralnetworks
🖊By Jo Stichbury
🔻So what does it take to become a data scientist? For some pointers on the skills for success, I interviewed Ben Chu, who is a Senior Data Scientist at Refinitiv Labs.
🔻Be curious
🔻Be scientific
🔻Be creative
🔻Learn how to code
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/think-like-data-scientist-data-analyst.html
#datascience #machinelearning
#tutorial #roadmap
#python #math #statistics #neuralnetworks
KDnuggets
How to Think Like a Data Scientist - KDnuggets
So what does it take to become a data scientist? For some pointers on the skills for success, I interviewed Ben Chu, who is a Senior Data Scientist at Refinitiv Labs.
📕 GPT-3: Language Models are Few-Shot Learners
⚪️ Github: https://github.com/openai/gpt-3
🔹Paper: https://arxiv.org/abs/2005.14165v1
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📌 Via: @cedeeplearning
#machinelearning #math
#deeplearning #neuralnetworks
#datascience #paper #github
⚪️ Github: https://github.com/openai/gpt-3
🔹Paper: https://arxiv.org/abs/2005.14165v1
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📌 Via: @cedeeplearning
#machinelearning #math
#deeplearning #neuralnetworks
#datascience #paper #github
GitHub
GitHub - openai/gpt-3: GPT-3: Language Models are Few-Shot Learners
GPT-3: Language Models are Few-Shot Learners. Contribute to openai/gpt-3 development by creating an account on GitHub.
⭕️ Top 12 R packages for ML in 2020
🔹do not miss out this nice article!
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📌Via: @cedeeplearning
https://analyticsindiamag.com/top-12-r-packages-for-machine-learning-in-2020/
#machinelearning #AI
#r #R_language #math
#neuralnetworks #skill
#deeplearning #datascience
🔹do not miss out this nice article!
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📌Via: @cedeeplearning
https://analyticsindiamag.com/top-12-r-packages-for-machine-learning-in-2020/
#machinelearning #AI
#r #R_language #math
#neuralnetworks #skill
#deeplearning #datascience
Analytics India Magazine
Top 12 R Packages For Machine Learning In 2020
R is one of the most prevalent programming languages for statistical analysis and computing. This article lists down top 12 R packages for ML.
🔹 Fundamentals of Data Analytics
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#datasicence #analytics #machinelearning #math #skills #resume #datamining #course
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#datasicence #analytics #machinelearning #math #skills #resume #datamining #course
🔹 Reinforcement Learning
Acme: A research framework for reinforcement learning
Github: https://github.com/deepmind/acme
Paper: https://arxiv.org/abs/2006.00979
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📌Via: @cedeeplearning
#deeplearning #machinelearning
#neuralnetworks #python #math
#statistics #reinforcement #Acme
Acme: A research framework for reinforcement learning
Github: https://github.com/deepmind/acme
Paper: https://arxiv.org/abs/2006.00979
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📌Via: @cedeeplearning
#deeplearning #machinelearning
#neuralnetworks #python #math
#statistics #reinforcement #Acme
⭕️ Fine-tuning ResNet with Keras, TensorFlow, and Deep Learning
In this tutorial, you will learn how to fine-tune #ResNet using #Keras, #TensorFlow, and Deep Learning.
https://www.pyimagesearch.com/2020/04/27/fine-tuning-resnet-with-keras-tensorflow-and-deep-learning/
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📌Via: @cedeeplearning
#machinelearning #AI
#deeplearning #neuralnetworks #math
#tutorial #free
In this tutorial, you will learn how to fine-tune #ResNet using #Keras, #TensorFlow, and Deep Learning.
https://www.pyimagesearch.com/2020/04/27/fine-tuning-resnet-with-keras-tensorflow-and-deep-learning/
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📌Via: @cedeeplearning
#machinelearning #AI
#deeplearning #neuralnetworks #math
#tutorial #free
PyImageSearch
Fine-tuning ResNet with Keras, TensorFlow, and Deep Learning - PyImageSearch
In this tutorial, you will learn how to fine-tune ResNet using Keras, TensorFlow, and Deep Learning.
deep_learning_computer_vision_principles_applications@NetworkArtificial.pdf
66.5 MB
📕 deep learning in computer vision
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📌Via: @cedeeplearning
#deeplearning #math #AI
#computer_vision #neuralnetworks
#machinelearning #datascience
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📌Via: @cedeeplearning
#deeplearning #math #AI
#computer_vision #neuralnetworks
#machinelearning #datascience
⭕️ OpenAI’s new language generator GPT-3 is shockingly good—and completely mindless
📌Via: @cedeeplearning
https://www.technologyreview.com/2020/07/20/1005454/openai-machine-learning-language-generator-gpt-3-nlp/
#deeplearning #gp3 #machinelearning #math
#neuralnetworks #AI #MIT
📌Via: @cedeeplearning
https://www.technologyreview.com/2020/07/20/1005454/openai-machine-learning-language-generator-gpt-3-nlp/
#deeplearning #gp3 #machinelearning #math
#neuralnetworks #AI #MIT
MIT Technology Review
OpenAI’s new language generator GPT-3 is shockingly good—and completely mindless
The AI is the largest language model ever created and can generate amazing human-like text on demand but won't bring us closer to true intelligence.
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⚪️ Basics of Neural Network Programming
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 26 Activation Functions
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #machinelearning #AI #coursera #free #python #math #activation_function #machinelearning #neuralnetworks
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 26 Activation Functions
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #machinelearning #AI #coursera #free #python #math #activation_function #machinelearning #neuralnetworks
⭕️ How You Should Read Research Papers According To Andrew Ng (Stanford Deep Learning Lectures)
Instructions on how to approach knowledge acquisition through published research papers by a recognized figure within the world of machine learning and education
🖊 by Richmond Alake
link: https://towardsdatascience.com/how-you-should-read-research-papers-according-to-andrew-ng-stanford-deep-learning-lectures-98ecbd3ccfb3
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📌Via: @cedeeplearning
#paper #research #stanford #deeplearning #andrew_ng
#neuralnetworks #math #machinelearning
Instructions on how to approach knowledge acquisition through published research papers by a recognized figure within the world of machine learning and education
🖊 by Richmond Alake
link: https://towardsdatascience.com/how-you-should-read-research-papers-according-to-andrew-ng-stanford-deep-learning-lectures-98ecbd3ccfb3
—————
📌Via: @cedeeplearning
#paper #research #stanford #deeplearning #andrew_ng
#neuralnetworks #math #machinelearning
Medium
How You Should Read Research Papers According To Andrew Ng (Stanford Deep Learning Lectures)
Instructions on how to approach knowledge acquisition through published research papers by a recognized figure.
Media is too big
VIEW IN TELEGRAM
⚪️ Basics of Neural Network Programming
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 27 Why Non-linear Activation Functions
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #machinelearning #AI #coursera #free #python #math #activation_function #machinelearning #neuralnetworks
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 27 Why Non-linear Activation Functions
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #machinelearning #AI #coursera #free #python #math #activation_function #machinelearning #neuralnetworks