Top 11 Jupyter Notebook GPU Projects
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Project mention: [D] What Repetitive Tasks Related to Machine Learning do You Hate Doing? | reddit.com/r/MachineLearning | 2022-02-21
There is already a ton of momentum around automating ML workflows. I would suggest you contribute to a preexisting project like, for instance, PyTorch Lightning or fast.ai.
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H2O
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
H2O.ai H2O is a deep learning tool built in Java. It supports most widely used machine learning algorithms and is a fast, scalable machine learning application interface used for deep learning, elastic net, logistic regression, and gradient boosting.
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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Looks like a nice project. I just bookmarked it to try sometime.
At a previous job, my boss wanted me to spend time on AutoML. I based my work on Google’s AdaNet [1] that did architecture search inside a single TensorFlow session. Unfortunately that project seems to have been abandoned.
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Project mention: All-in-One Docker Based IDE for Data Science and ML | news.ycombinator.com | 2021-09-24
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adaptnlp
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Project mention: Tools to use for Semantic-searching Question Answering System | reddit.com/r/learnprogramming | 2022-04-23Check out adaptnlp
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SonarLint
Deliver Cleaner and Safer Code - Right in Your IDE of Choice!. SonarLint is a free and open source IDE extension that identifies and catches bugs and vulnerabilities as you code, directly in the IDE. Install from your favorite IDE marketplace today.
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Project mention: TensorFlow Metal Back End on Apple Silicon Experiments (Just for Fun) | news.ycombinator.com | 2021-11-15
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aws-virtual-gpu-device-plugin
AWS virtual gpu device plugin provides capability to use smaller virtual gpus for your machine learning inference workloads
This project (available here) uses the k8s device plugin described by this AWS blog post to make GPU-based nodes publish the amount of GPU resource they have available. Instead of the amount of VRAM available or some abstract metric, this plugin advertises the amount of pods/processes that can be connected to the GPU. This is controlled by what is called by NVIDIA as Multi-Process Service (MPS).
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I created something that lets you get free GPU on VS Code with Google Colab with just 1-click. Have a look at https://github.com/DerekChia/colab-vscode
This is my default go-to as a poor man ML setup, with environment and dependencies set up automatically via bash script on start up.
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git clone https://github.com/iterative/blog-tpi-jupyter cd blog-tpi-jupyter export NGROK_TOKEN="..." # Signup for free at https://ngrok.com terraform init # Setup local dependencies terraform apply # Create cloud resources & upload workdir terraform refresh # Get URLs (rerun if blank)
Jupyter Notebook GPU related posts
- Use Free GPU on VS Code with Google Colab
- Good practices for neural network training: identify, save, and document best models
- Run VS Code on Google Colab with 1-click
- TensorFlow Metal Back End on Apple Silicon Experiments (Just for Fun)
- [D] Serverless solutions for GPU inference (if there's such a thing)
- D I Refuse To Use Pytorch Because Its A Facebook
Index
What are some of the best open-source GPU projects in Jupyter Notebook? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | fastai | 22,238 |
| 2 | H2O | 5,812 |
| 3 | pycaret | 5,624 |
| 4 | adanet | 3,396 |
| 5 | ML-Workspace | 2,545 |
| 6 | TrainYourOwnYOLO | 575 |
| 7 | adaptnlp | 394 |
| 8 | tf-metal-experiments | 143 |
| 9 | aws-virtual-gpu-device-plugin | 111 |
| 10 | colab-vscode | 36 |
| 11 | blog-tpi-jupyter | 2 |
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