Top 23 Python Kera Projects
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
data science ipython notebooks
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Project mention: Open source - that means free to use commercially right? ... right? | reddit.com/r/deepdream | 2021-12-04
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Scout APM
Scout APM: A developer's best friend. Try free for 14-days. Scout APM uses tracing logic that ties bottlenecks to source code so you know the exact line of code causing performance issues and can get back to building a great product faster.
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If you just want to run tensorflow or pytorch for a Jupyter notebook, setting the environment shouldn't be difficult. I know that AWS has a marketplace of preconfigured images. However, you can go as advanced as setting up a cluster of gpu-equipped nodes to setup Horovod (https://github.com/horovod/horovod) to do distributed machine learning. Yes, there's a learning curve, but you cannot acquire this skillet any other way.
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d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.
Project mention: I created a way to learn machine learning through Jupyter | reddit.com/r/learnmachinelearning | 2021-04-30There are actually some online books and courses built on Jupyter Notebook ([Dive to Deep Learning Book](https://github.com/d2l-ai/d2l-en) for example). However yours is more detail and could really helps beginners.
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I think the interfaces aren't high level enough for the average programmer to adopt it. It needs what https://autokeras.com is for neural nets.
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MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. (by microsoft)
Project mention: [D] Tools for converting TF code to Pytorch | reddit.com/r/MachineLearning | 2021-02-01 -
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textgenrnn
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
Project mention: I trained a neural network on every town and village name in England and then made a website that lets you generate them | reddit.com/r/unitedkingdom | 2021-08-30This is an utterly fantastic question but I actually don't understand much about neural nets at all, and am just using a prebuilt python library is basically text based neural nets for idiots (https://github.com/minimaxir/textgenrnn) Happy to share data though if you want to find this out and would know how?
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Project mention: [Discussion] Why are Einstein Sum Notations not popular in ML? They changed my life. | reddit.com/r/MachineLearning | 2021-12-04
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client
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API. (by wandb)
Project mention: [D] What is your ML experiment workflow? Discussion on training a model to the Latex tables | reddit.com/r/MachineLearning | 2021-10-20My current experimental setup is running experiments on a machine with a GPU, then collecting results to Weights and Biases (https://wandb.ai/), then to Latex tables. I'm trying to automate as much as possible since collecting results takes time and to make things easier.
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Project mention: Anyone implemented latest image segmentation models/tuning from cvpr 2021? | reddit.com/r/learnmachinelearning | 2021-07-02
I am doing an image segmentation project using https://github.com/qubvel/segmentation_models as the baseline. I was wondering if any of you have tried the latest segmentation models from cvpr papers. If yes, which ones you found to be interesting or actually improve miou. And how difficult/easy it is to implement those?
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This could be because of session thats is running in background which you need to terminate and refresh.Or it might be due to large nn model so maybe try changing the number of layers and neurons in the model.This summary library might help you check the size of your nn model
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image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Project mention: What’s an extremely useful website most people probably don’t know about? | reddit.com/r/AskReddit | 2021-11-19 -
Project mention: [D] Productionalizing machine learning pipelines for small teams | reddit.com/r/MachineLearning | 2021-08-08
For running experiments, http://polyaxon.com/ is a really good free open-source package that has lots of nice integrations so you can quickly run experiments in k8s but it might be overkill in some cases.
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deepface
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
Project mention: [OC] Median faces from different porn subreddits | reddit.com/r/dataisbeautiful | 2021-08-09I scraped images from the different subreddits, then used the deepface python library to extract and align the faces. I used Imagemagick to display them in a grid. The top-left image is an average of all the faces collected. I also tried the mean faces, but the median faces resulted in better details and less washed-out colors.
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Project mention: tf-based framework for graph neural networks? | reddit.com/r/tensorflow | 2021-11-05
Has any library emerged as the clear leader in the TensorFlow Graph Neural Network space? A quick search revealed Spektral.
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Project mention: Simplest way to deploy Keras NN model into C++? | reddit.com/r/learnmachinelearning | 2021-08-29
Don't know about simplest, but we either used caffe or tensorrt, it is maybe a bit difficult to use but I'd actually say simple fast GPU inference is what it's geared towards. There is a keras -> caffe converter https://github.com/pierluigiferrari/ssd_keras here, I think. Caffe is a c++ lib, typical, with dependencies and all. I've never heard anything of tensorflow running on c++. But with tensorrt you should get an "artifact" that you'd load, no matter where it comes from
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image-quality-assessment
Convolutional Neural Networks to predict the aesthetic and technical quality of images.
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Project mention: Why do all image to text conversion tools work based on brightness and not finding the most similar character? | reddit.com/r/asciiart | 2021-09-08
Not all. See for example DeepAA.
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PINTO_model_zoo
A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]
Check it out https://github.com/PINTO0309/PINTO_model_zoo
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model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
Project mention: Need Help With Pruning Model Weights in Tensorflow 2 | reddit.com/r/tensorflow | 2021-06-07I have been following the example shown here, and so far I've had mixed results and wanted to ask for some help because the resources I've found online have not been able to answer some of my questions (perhaps because some of these are obvious and I am just being dumb).
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Project mention: Cannot understand how REINFORCE model is trained | reddit.com/r/reinforcementlearning | 2021-03-04
I have understood the concept of REINFORCE algorithm and what policy gradient is. However, when I see the code published by PacktPublishing, I was stuck with it.
Python Keras related posts
- Open source - that means free to use commercially right? ... right?
- Generating faces from "illegal" parameters using an older AI architecture. (CNN, not GAN.)
- Creating a training set for the MaskRCNN
- [D] What is your ML experiment workflow? Discussion on training a model to the Latex tables
- MIT CSAIL, TU Wien, and IST Researchers Introduce Deep Learning Models That Require Fewer Neurons
- What got you into learning ML?
- [Research]Biologically-inspired Neural Networks for Self-Driving Cars
Index
What are some of the best open-source Kera projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | data-science-ipython-notebooks | 21,875 |
| 2 | Mask_RCNN | 20,983 |
| 3 | horovod | 11,898 |
| 4 | d2l-en | 11,648 |
| 5 | autokeras | 8,250 |
| 6 | best-of-ml-python | 5,976 |
| 7 | MMdnn | 5,468 |
| 8 | textgenrnn | 4,574 |
| 9 | einops | 3,914 |
| 10 | client | 3,551 |
| 11 | segmentation_models | 3,550 |
| 12 | pytorch-summary | 3,334 |
| 13 | image-super-resolution | 3,263 |
| 14 | polyaxon | 2,959 |
| 15 | deepface | 2,804 |
| 16 | spektral | 1,931 |
| 17 | InvoiceNet | 1,876 |
| 18 | ssd_keras | 1,765 |
| 19 | image-quality-assessment | 1,469 |
| 20 | DeepAA | 1,341 |
| 21 | PINTO_model_zoo | 1,250 |
| 22 | model-optimization | 1,159 |
| 23 | Advanced-Deep-Learning-with-Keras | 1,145 |
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