keras-ncp
MMdnn
| keras-ncp | MMdnn | |
|---|---|---|
| 5 | 3 | |
| 150 | 5,780 | |
| - | 0.1% | |
| 0.0 | 0.0 | |
| over 1 year ago | 7 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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keras-ncp
- A brain-inspired intelligent agent that learns to control an autonomous vehicle directly from its camera inputs (end-to-end learning to control)
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MIT CSAIL, TU Wien, and IST Researchers Introduce Deep Learning Models That Require Fewer Neurons
Quick 5 Min Read | Paper| Github | MIT Blog
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What got you into learning ML?
One particular example that I really like is this research that used the biological neural circuitry of a nematode for less computationally expensive models, but with the same level of performance as other normal models. Also the application of attention in human brains to neural networks, which achieves really great results, like the popular GPT-3 by OpenAI .
- [Research]Biologically-inspired Neural Networks for Self-Driving Cars
MMdnn
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[R] Importing TensorFlow neural networks stored as *.h5
The only way I found online is to convert the *.h5 files to MXNet files using Microsoft model management of deep neural networks (link)
- [D] Tools for converting TF code to Pytorch
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Apple’s New M1 Chip is a Machine Learning Beast
Yes. But that's missing the point. Almost everything in the space uses a framework other than Core ML. Therefore most people need good development support for PyTorch/Tensorflow etc., not Core ML. The fact that Apple has a tool to import/convert models is nice, but not relevant. Also, there is onnx as an exchange format between the frameworks, and tools like MMdnn and others.
What are some alternatives?
autokeras - AutoML library for deep learning
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
keras-onnx - Convert tf.keras/Keras models to ONNX
redisai-examples - RedisAI showcase
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
torchinfo - View model summaries in PyTorch!
coremltools - Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
deepo - Setup and customize deep learning environment in seconds.
PINTO_model_zoo - A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.