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Top 23 Jupyter Notebook AI Projects
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Project mention: [D] Querying with multiple vectors during embedding nearest neighbor search? | reddit.com/r/MachineLearning | 2023-02-03
That was an interesting read, but I don't think it solves my problem. Their examples don't show joint vector searches: https://github.com/google-research/google-research/blob/master/scann/docs/example.ipynb
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Project mention: Object detection with depth measurement using pre-trained models with OAK-D | reddit.com/r/computerscience | 2022-04-29
Code Link : https://github.com/spmallick/learnopencv/tree/master/OAK-Object-Detection-with-Depth
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SonarLint
Clean code begins in your IDE with SonarLint. Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today.
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dopamine
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
You can also reference the source code for some of the popular implementations from open source RL libraries like stablebaselines3, RLlib, CleanRL, or Dopamine. These can help you if you’re trying to compare your implementation to a “standard”.
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You'd want to use an NLP method for this as in order to determine optimal homonyms there would have to be some method of deriving context from the words ahead of and behind the substitution. Take a look at nlpaug.
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Project mention: Is there a AI that is able to turn normal pictures in that kind of pictures or that I am able to plott them with my pen-plotter? | reddit.com/r/artificial | 2022-04-25
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machine-learning-experiments
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Project mention: [D] Have researchers given up on traditional machine learning methods? | reddit.com/r/MachineLearning | 2023-01-31- all domains requiring high interpretability absolutely ignore deep learning at all, and put all their research into traditional ML; see e.g. counterfactual examples, important interpretability methods in finance, or rule-based learning, important in medical or law applications
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Hehe, well you know, PR welcome, the front end is 500 lines https://github.com/rom1504/clip-retrieval/blob/main/front/sr...
Other people have done a few alternate front ends already
This one is meant to be functional, but could sure be made prettier
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Deep-Learning-In-Production
Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
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tensor-house
A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain
I still have this on my reading list, it has quite some interesting SC applications. https://github.com/ikatsov/tensor-house
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PConv-Keras
Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai
Recently I came across Partial Convolutions for Image Inpainting using Keras and spent a few days playing with the Jupyter notebooks included in the repo. I tried hard to reverse engineer everything in an effort to learn, but my limited experience with deep learning neural networks left me unable to accomplish anything.
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vertex-ai-samples
Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
She made mentions to ML-Ops and MLFlow including Vertex AI the GCP implementation. I will post the video as soon as it is available. In the meantime, you can enjoy any other talk from Nerea Luis
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Basic-Mathematics-for-Machine-Learning
The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI
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cleora
Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.
Project mention: Cleora - an ultra fast graph embedding tool written in Rust | reddit.com/r/u_maoxiangsun | 2022-07-06 -
Workshops
Workshops organized to introduce students to security, AI, AR/VR, hardware and software (by PoCInnovation)
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Project mention: Hi friends, we bring you the first bilingual ChatGPT detection toolset and would love your feedback~ | reddit.com/r/deeplearning | 2023-01-11
Project GitHub page: ChatGPT Comparison Corpus (C3), Detectors, and more! 🔥
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GitHub
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Project mention: [D] DL Practitioners, Do You Use Layer Visualization Tools s.a GradCam in Your Process? | reddit.com/r/MachineLearning | 2022-10-28
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conformal_classification
Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
Project mention: [P] 🚀 AWS launches Fortuna, an open-source library for Uncertainty Quantification | reddit.com/r/MachineLearning | 2023-01-04What is the best end-to-end example showing it? https://github.com/awslabs/fortuna/blob/main/examples/mnist_classification.ipynb ? It would be nice to have some visual explainer, as in https://github.com/aangelopoulos/conformal_classification .
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Project mention: DCGAN (CIFAR-10) Generating fake images is easy, but how to also output the class label (1 to 10) with the fake generated images? | reddit.com/r/learnmachinelearning | 2022-03-13
I have this DCGAN model (https://github.com/csinva/gan-vae-pretrained-pytorch/tree/master/cifar10_dcgan) which generates fake Cifar-10 images. However I also want to get the intended class label output with the fake generated images. How can I do this? This model which I found only generates fake images but doesn't know what class the generated images belong to.
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oemer
End-to-end Optical Music Recognition (OMR) system. Transcribe phone-taken music sheet image into MusicXML, which can be edited and converted to MIDI.
Project mention: Optical music recognition system with deep learning | reddit.com/r/u_waynerad | 2022-02-08 -
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
The latest post mention was on 2023-02-03.
Jupyter Notebook AI related posts
- [D] Querying with multiple vectors during embedding nearest neighbor search?
- Any good resource on self-supervised monocular depth estimation
- Artificial Intelligence course
- Is there something like ChatGPT but with image recognition?
- Deep Learning Pioneer Geoffrey Hinton Publishes New Deep Learning Algorithm
- Is this a fucking paywall?
- Is there a way to use clip or blip to search a massive collection of images for specific things within the picture?
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www.saashub.com | 4 Feb 2023
Index
What are some of the best open-source AI projects in Jupyter Notebook? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | google-research | 27,040 |
| 2 | learnopencv | 17,848 |
| 3 | dopamine | 9,994 |
| 4 | AI-For-Beginners | 4,917 |
| 5 | nlpaug | 3,783 |
| 6 | ArtLine | 3,300 |
| 7 | machine-learning-experiments | 1,371 |
| 8 | imodels | 1,024 |
| 9 | clip-retrieval | 938 |
| 10 | Deep-Learning-In-Production | 882 |
| 11 | tensor-house | 879 |
| 12 | PConv-Keras | 872 |
| 13 | vertex-ai-samples | 587 |
| 14 | Basic-Mathematics-for-Machine-Learning | 452 |
| 15 | cleora | 404 |
| 16 | Workshops | 351 |
| 17 | chatgpt-comparison-detection | 344 |
| 18 | Diffusion-ColabUI | 292 |
| 19 | TorchDrift | 271 |
| 20 | LessonMaterials | 162 |
| 21 | conformal_classification | 159 |
| 22 | gan-vae-pretrained-pytorch | 141 |
| 23 | oemer | 139 |
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SaaSHub helps you find the best software and product alternatives
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