Neuromorphic-Computing-Guide
Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures. (by mikeroyal)
Shallow-learning
Replicating brain's low energy high efficiency model architecture & calculating (maths) (by sleepingcat4)
| Neuromorphic-Computing-Guide | Shallow-learning | |
|---|---|---|
| 10 | 1 | |
| 252 | 2 | |
| - | - | |
| 5.0 | 2.4 | |
| 4 months ago | about 1 year ago | |
| Python | Python | |
| - | Apache License 2.0 |
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Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Neuromorphic-Computing-Guide
Posts with mentions or reviews of Neuromorphic-Computing-Guide.
We have used some of these posts to build our list of alternatives
and similar projects.
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I am extremely interested second language acquisition and Artificial intelligence. How can I get into research?
Start reading papers on https://www.biorxiv.org/ and notice what seems most interesting or promising to you. Learn python. There are actually quite a few open source "into to machine learning" courses - maybe start with MIT's Learning Library, see what you find there. I also have this bookmarked for myself for later; I'm sure there are a few more goodies worth checking out here: https://github.com/mikeroyal/Neuromorphic-Computing-Guide
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Getting Started with Neuromorphic Computing
Tools and Resources for getting started with Neumorphic Computing. The process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.
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Neuromorphic Engineering
Neuromorphic engineering, which combines electrical, computer, and mechanical engineering with biology, physics, and neuroscience. uses specialized computing architectures that reflect the structure (morphology) of neural networks from the bottom up: dedicated processing units emulate the behavior of neurons directly in hardware, and a web of physical interconnections (bus-systems) facilitate the rapid exchange of information. Useful Tools and Resources for learning about Neuromorphic engineering.
- GitHub - mikeroyal/Neuromorphic-Computing-Guide: Neuromorphic Computing Guide
- Neuromorphic Computing that enables fast and power-efficient neural network–based artificial intelligence
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Neuromorphic Computing
Neuromorphic computing models the way the brain works through spiking neural networks and other types of neural networks. Useful Tools and Resources for learning about Neuromorphic Computing.
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Tools and Resources for Neuromorphic Computing
Useful Tools and Resources for learning about Neuromorphic Computing. Neuromorphic computing models the way the brain works through spiking neural networks and other types of neural networks.
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Tools and Resource for Neuromorphic Computing
UsefuleTools and Resource for about Neuromorphic Computing.
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Cool Neuromorphic Computing Guide/Wiki
Neuromorphic Computing Guide/Wiki: https://github.com/mikeroyal/Neuromorphic-Computing-Guide
Shallow-learning
Posts with mentions or reviews of Shallow-learning.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Shallow Deep Learning Models and Complexity Calculation - A TensorFlow Project Implementation
If you're interested in learning more about shallow deep learning models or just want to play around with some code, feel free to check out my project on GitHub: https://github.com/sleepingcat4/Shallow-learning. I'd love to hear your thoughts and feedback on the project, so feel free to comment or reach out to me directly.
What are some alternatives?
When comparing Neuromorphic-Computing-Guide and Shallow-learning you can also consider the following projects:
norse - Deep learning with spiking neural networks (SNNs) in PyTorch.
braindecode - Deep learning software to decode EEG, ECG or MEG signals
lava - A Software Framework for Neuromorphic Computing
faceswap - Deepfakes Software For All
Spiking-Neural-Network - Pure python implementation of SNN
snntorch - Deep and online learning with spiking neural networks in Python
spaCy - đź’« Industrial-strength Natural Language Processing (NLP) in Python
TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD
NIPY - Workflows and interfaces for neuroimaging packages
keras - Deep Learning for humans [Moved to: https://github.com/keras-team/keras]
Nerve - This is a basic implementation of a neural network for use in C and C++ programs. It is intended for use in applications that just happen to need a simple neural network and do not want to use needlessly complex neural network libraries.
Keras - Deep Learning for humans
Neuromorphic-Computing-Guide vs norse
Shallow-learning vs braindecode
Neuromorphic-Computing-Guide vs lava
Shallow-learning vs faceswap
Neuromorphic-Computing-Guide vs Spiking-Neural-Network
Shallow-learning vs snntorch
Neuromorphic-Computing-Guide vs spaCy
Shallow-learning vs TorchGA
Neuromorphic-Computing-Guide vs NIPY
Shallow-learning vs keras
Neuromorphic-Computing-Guide vs Nerve
Shallow-learning vs Keras