🧠 Topic: dopamine system
💠 Link: https://psychscenehub.com/psychinsights/the-dopamine-hypothesis-of-schizophrenia/
💡 Tags: #neuroscience
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💠 Link: https://psychscenehub.com/psychinsights/the-dopamine-hypothesis-of-schizophrenia/
💡 Tags: #neuroscience
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Psych Scene Hub
Dopamine Hypothesis of Schizophrenia: Neurobiology and Clinical Insights
Understand the dopamine hypothesis of schizophrenia, its neurobiological basis, clinical implications, and key dopamine pathways involved in psychosis.
🧠 Topic: All You Need To Know For Your First Ever Project in PyTorch !
💠 Link: https://medium.com/@nikhilamunipalli/starter-pack-for-deep-learning-in-pytorch-for-extreme-beginners-by-a-beginner-330f3fdefcc4
💡 Tags: #pytorch
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💠 Link: https://medium.com/@nikhilamunipalli/starter-pack-for-deep-learning-in-pytorch-for-extreme-beginners-by-a-beginner-330f3fdefcc4
💡 Tags: #pytorch
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Medium
All You Need To Know For Your First Ever Project in PyTorch !
Welcome deep learning learners! This article is a kick start for your first ever deep learning model in pytorch.
🧠 Topic: Review — SKNet: Selective Kernel Networks (Image Classification)
💠 Link: https://sh-tsang.medium.com/review-sknet-selective-kernel-networks-image-classification-63ebbad7d78f
💡 Tags: #computer_vision #neuroscience #cnn #deep_learning
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💠 Link: https://sh-tsang.medium.com/review-sknet-selective-kernel-networks-image-classification-63ebbad7d78f
💡 Tags: #computer_vision #neuroscience #cnn #deep_learning
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Medium
Review — SKNet: Selective Kernel Networks (Image Classification)
Attention Branch for Various Kernel Sizes, Outperforms SENet
🧠 Topic: Stock predictions with state-of-the-art Transformer and Time Embeddings
💠 Link: https://towardsdatascience.com/stock-predictions-with-state-of-the-art-transformer-and-time-embeddings-3a4485237de6
💡 Tags: #artificial_intelligence #deep_learning
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💠 Link: https://towardsdatascience.com/stock-predictions-with-state-of-the-art-transformer-and-time-embeddings-3a4485237de6
💡 Tags: #artificial_intelligence #deep_learning
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🧠 Topic: Comprehensive Guide to Different Pooling Layers in Deep Learning
💠 Link: https://analyticsindiamag.com/comprehensive-guide-to-different-pooling-layers-in-deep-learning/
💡 Tags: #artificial_intelligence #deep_learning
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💠 Link: https://analyticsindiamag.com/comprehensive-guide-to-different-pooling-layers-in-deep-learning/
💡 Tags: #artificial_intelligence #deep_learning
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Analytics India Magazine
Comprehensive Guide to Different Pooling Layers in Deep Learning
we use pooling layers for downsampling the data by extracting important features from the data . commonly used in CNN with convolutional layer
🧠 Topic: Attention is all you need
💠 Link: https://becominghuman.ai/attention-is-all-you-need-16bf481d8b5c
💡 Tags: #artificial_intelligence #deep_learning #nlp
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💠 Link: https://becominghuman.ai/attention-is-all-you-need-16bf481d8b5c
💡 Tags: #artificial_intelligence #deep_learning #nlp
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Becoming Human
A New Era in Deep Learning: Understanding Transformer Models
An explanation about transformer
🧠 Topic: The Illustrated Transformer
💠 Link: https://jalammar.github.io/illustrated-transformer/
💡 Tags: #artificial_intelligence #deep_learning #nlp
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💠 Link: https://jalammar.github.io/illustrated-transformer/
💡 Tags: #artificial_intelligence #deep_learning #nlp
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jalammar.github.io
The Illustrated Transformer
Discussions:
Hacker News (65 points, 4 comments), Reddit r/MachineLearning (29 points, 3 comments)
Translations: Arabic, Chinese (Simplified) 1, Chinese (Simplified) 2, French 1, French 2, Italian, Japanese, Korean, Persian, Russian, Spanish 1, Spanish…
Hacker News (65 points, 4 comments), Reddit r/MachineLearning (29 points, 3 comments)
Translations: Arabic, Chinese (Simplified) 1, Chinese (Simplified) 2, French 1, French 2, Italian, Japanese, Korean, Persian, Russian, Spanish 1, Spanish…
🧠 Topic: Python Type Checking (Guide)
💠 Link: https://realpython.com/python-type-checking/#playing-with-python-types-part-1
💡 Tags: #python
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💠 Link: https://realpython.com/python-type-checking/#playing-with-python-types-part-1
💡 Tags: #python
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Realpython
Python Type Checking (Guide) – Real Python
In this guide, you'll look at Python type checking. Traditionally, types have been handled by the Python interpreter in a flexible but implicit way. Recent versions of Python allow you to specify explicit type hints that can be used by different tools to…
🧠 Topic: 5 gradient/derivative related PyTorch functions
💠 Link: https://attyuttam.medium.com/5-gradient-derivative-related-pytorch-functions-8fd0e02f13c6
💡 Tags: #pytorch
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💠 Link: https://attyuttam.medium.com/5-gradient-derivative-related-pytorch-functions-8fd0e02f13c6
💡 Tags: #pytorch
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Medium
5 gradient/derivative related PyTorch functions
In this article, I will be talking about the 5 PyTorch functions that I have studied through. Examples will be provided along with…
🧠 Topic: PyTorch Template Project
💠 Link: https://github.com/victoresque/pytorch-template
💡 Tags: #pytorch
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💠 Link: https://github.com/victoresque/pytorch-template
💡 Tags: #pytorch
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GitHub
GitHub - victoresque/pytorch-template: PyTorch deep learning projects made easy.
PyTorch deep learning projects made easy. Contribute to victoresque/pytorch-template development by creating an account on GitHub.
🧠 Topic: A Comprehensive Guide to Image Processing
💠 Link: https://towardsdatascience.com/image-processing-part-2-1fb84931364a
💡 Tags: #computer_vision
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💠 Link: https://towardsdatascience.com/image-processing-part-2-1fb84931364a
💡 Tags: #computer_vision
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Medium
Image Processing Part 2
2.1 : Non Linear Spatial Filtering, Min, Max & Median Filters with Python Implementation from Scratch 2.2 : Linear Spatial Filtering…
🧠 Topic: Python for High Performance: Python Containers
💠 Link: https://cvw.cac.cornell.edu/python/containers
💡 Tags: #python
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💠 Link: https://cvw.cac.cornell.edu/python/containers
💡 Tags: #python
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🧠 Topic: How to Manually Scale Image Pixel Data for Deep Learning
💠 Link: https://machinelearningmastery.com/how-to-manually-scale-image-pixel-data-for-deep-learning/
💡 Tags: #python #scaling #preprocessing #standardization #normalization #centring
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💠 Link: https://machinelearningmastery.com/how-to-manually-scale-image-pixel-data-for-deep-learning/
💡 Tags: #python #scaling #preprocessing #standardization #normalization #centring
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🧠 Topic: Why normalize images by subtracting dataset's image mean, instead of the current image mean in deep learning?
💠 Link: https://stats.stackexchange.com/questions/211436/why-normalize-images-by-subtracting-datasets-image-mean-instead-of-the-current
💡 Tags: #python #scaling #preprocessing #standardization #normalization #centring
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💠 Link: https://stats.stackexchange.com/questions/211436/why-normalize-images-by-subtracting-datasets-image-mean-instead-of-the-current
💡 Tags: #python #scaling #preprocessing #standardization #normalization #centring
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Cross Validated
Why normalize images by subtracting dataset's image mean, instead of the current image mean in deep learning?
There are some variations on how to normalize the images but most seem to use these two methods:
Subtract the mean per channel calculated over all images (e.g. VGG_ILSVRC_16_layers)
Subtract by pi...
Subtract the mean per channel calculated over all images (e.g. VGG_ILSVRC_16_layers)
Subtract by pi...
🧠 Topic: A Gentle Introduction to Graph Neural Networks
💠 Link: https://distill.pub/2021/gnn-intro/
💡 Tags: #GNN
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💠 Link: https://distill.pub/2021/gnn-intro/
💡 Tags: #GNN
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Distill
A Gentle Introduction to Graph Neural Networks
What components are needed for building learning algorithms that leverage the structure and properties of graphs?
🧠 Topic: Let’s code a Neural Network in plain NumPy
💠 Link: https://towardsdatascience.com/lets-code-a-neural-network-in-plain-numpy-ae7e74410795
💡 Tags: #artificial_intelligence #deep_learning #python
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💠 Link: https://towardsdatascience.com/lets-code-a-neural-network-in-plain-numpy-ae7e74410795
💡 Tags: #artificial_intelligence #deep_learning #python
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Medium
Let’s code a Neural Network in plain NumPy
Mysteries of Neural Networks Part III
🧠 Topic: How to implement a neural network step to step guide using numpy
💠 Link: https://peterroelants.github.io/posts/neural-network-implementation-part01/
💡 Tags: #artificial_intelligence #deep_learning #python
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💠 Link: https://peterroelants.github.io/posts/neural-network-implementation-part01/
💡 Tags: #artificial_intelligence #deep_learning #python
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Peter’s Notes
How to implement a neural network (1/5) - gradient descent
How to implement, and optimize, a linear regression model from scratch using Python and NumPy. The linear regression model will be approached as a minimal regression neural network. The model will be optimized using gradient descent, for which the gradient…
🧠 Topic: Understanding Autograd: 5 Pytorch tensor functions
💠 Link: https://medium.com/@namanphy/understanding-autograd-5-pytorch-tensor-functions-8f47c27dc38
💡 Tags: #python #pytorch
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💠 Link: https://medium.com/@namanphy/understanding-autograd-5-pytorch-tensor-functions-8f47c27dc38
💡 Tags: #python #pytorch
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Medium
Understanding Autograd : 5 pytorch tensor functions
Understanding the Pytorch Autograd module with the help of 5 important tensor functions.
🧠 Topic: Welcome to the UvA Deep Learning Tutorials!
💠 Link: https://uvadlc-notebooks.readthedocs.io/en/latest/index.html
💡 Tags: #deep_learning
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💠 Link: https://uvadlc-notebooks.readthedocs.io/en/latest/index.html
💡 Tags: #deep_learning
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🧠 Topic: 10 Must-read AI Papers
💠 Link: https://blog.crossminds.ai/post/must-read-ai-papers-neural-networks-computer-vision-deep-learning-nlp-machine-learning
💡 Tags: #deep_learning
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💠 Link: https://blog.crossminds.ai/post/must-read-ai-papers-neural-networks-computer-vision-deep-learning-nlp-machine-learning
💡 Tags: #deep_learning
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🧠 Topic: A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
💠 Link: https://towardsdatascience.com/a-gentle-introduction-to-graph-neural-network-basics-deepwalk-and-graphsage-db5d540d50b3
💡 Tags: #deep_learning #gnn
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💠 Link: https://towardsdatascience.com/a-gentle-introduction-to-graph-neural-network-basics-deepwalk-and-graphsage-db5d540d50b3
💡 Tags: #deep_learning #gnn
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Medium
A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
Recently, Graph Neural Network (GNN) has gained increasing popularity in various domains, including social network, knowledge graph…