Top 23 Jupyter Notebook Artificial intelligence Projects
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Project mention: How is accuracy calculated in multi label classification | reddit.com/r/MLQuestions | 2022-01-31
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My favourite book on algorithmic trading is Machine Learning for Algorithmic Trading by Stefan Jansen. Or anything by Ernest Chan.
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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Project mention: Contextual Similarity between a list of n-grams and a website | reddit.com/r/MLQuestions | 2022-06-11
3) Use deep contextual models with wordpiecing/BPE tokenizers- like all the models: BERT, RoBERTA, etc. On the simpler side, could also swap words with synonyms, which is easy to do with this library: https://github.com/makcedward/nlpaug. Instead of a single n-gram per topic, it might be nice to have a bundle of related words- you could play around with wordnet and see if that's helpful- also easy to do w/ nlpaug.
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Reinforcement-Learning
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning (by andri27-ts)
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Data-science
Collection of useful data science topics along with code and articles (by khuyentran1401)
Project mention: Half of women will get a false positive 3D mammogram, study finds | news.ycombinator.com | 2022-03-25And if you can't to positive tests and were each time randomly selected for the test, the probability to be really positive is 99%
https://github.com/khuyentran1401/Data-science/blob/master/s...
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Project mention: Announcing a New Free Curriculum: Artificial Intelligence for Beginners | dev.to | 2022-05-26
Students can use this curriculum to learn the basics of AI and Neural Networks. In addition to text-based lessons, there are executable Jupyter Notebooks with samples, as well as labs that you can do to deepen your knowledge. You can run notebooks either on your local computer or in the cloud. Join your peers on GitHub Discussion Boards to learn together and watch for more learning opportunities online.
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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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machine-learning-experiments
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
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imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Option 2) fit a model from https://github.com/csinva/imodels on the predicted values of the RF
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100DaysofMLCode
My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
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Fast-Transformer
An implementation of Fastformer: Additive Attention Can Be All You Need, a Transformer Variant in TensorFlow
Project mention: I implemented Fastformer: Additive Attention in TensorFlow | reddit.com/r/tensorflow | 2021-12-27 -
Project mention: A minimal standalone example of diffusion model | news.ycombinator.com | 2022-06-09
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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: [R] Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification - Link to a free online lecture by the author in comments | reddit.com/r/MachineLearning | 2022-03-06Uncertainty Sets for Image Classifiers using Conformal Prediction https://arxiv.org/abs/2009.14193 https://github.com/aangelopoulos/conformal_classification
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CenterSnap
Pytorch code for ICRA'22 paper: "Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation"
Project mention: In A Latest Computer Vision Research, Researchers Propose ShAPO; An End-To-End Method For Joint Multi-Object Detection, 3D Textured Reconstruction, 6D Object Pose, And Size Estimation | reddit.com/r/computervision | 2022-08-07Continue reading | Check out the paper, github link and project page.
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artificial-intelligence-and-machine-learning
A repository for implementation of artificial intelligence algorithm which includes machine learning and deep learning algorithm as well as classical AI search algorithm
Project mention: Perceptron Algorithm from Scratch in Python | reddit.com/r/programming | 2022-01-12Thanks, you can check out the github repository if needed!
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Thanks for your question. Yes, we did research the space a lot before making AutoAI. Here is what we found:
PyCaret: Semi-automatic. You do the first run; then you figure the next set of runs. Ensemble models require manual configuration.
Tpot: Does a great job. Generates 4-5 lines of py code too. But does not support Neural Networks / DNN. So works only for problems where GOFAI works.
H2O.ai: They have an open-source flavor, but the best way to use it is the enterprise version on the H2O cloud. The interface is confusing, and the final output is black-box.
Now there are many in the enterprise category, such as DataRobot, AWS SageMaker, Azure etc. Most are unaffordable to Data Scientists unless your employer is sponsoring the platform.
AutoAI: This is 100% automated. Uses GOFAI, Neural Networks and DNN, all in one box. It is 100% White-box. It is the only AutoML framework that generates high-quality (1000s of lines) of Jupyter Notebook code. You can check some example codes here: https://cloud.blobcity.com
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language-planner
Official Code for "Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents"
Project mention: [D] Paper Discussion Video - Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents (+Author Interview) | reddit.com/r/MachineLearning | 2022-02-08 -
tabular-dl-num-embeddings
The official implementation of the paper "On Embeddings for Numerical Features in Tabular Deep Learning"
Project mention: [R] New paper on Tabular DL: "On Embeddings for Numerical Features in Tabular Deep Learning" | reddit.com/r/MachineLearning | 2022-03-17JFYI: recently, we have split our codebase into separate projects: - https://github.com/Yura52/rtdl - https://github.com/Yura52/tabular-dl-revisiting-models - (the new one) https://github.com/Yura52/tabular-dl-num-embeddings
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Project mention: New Opensource Hotword Detector : EfficientWord-Net | reddit.com/r/raspberry_pi | 2021-11-10
Github Link : https://github.com/Ant-Brain/EfficientWord-Net
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Social_Distancing_with_AI
Monitor people violating Social Distancing or not wearing Face Masks in public through CCTV footage.
I was applying [this project](https://github.com/rohanrao619/Social_Distancing_with_AI) to some local CCTV footage I have. Came out real nice. TLDR - it's an AI that tracks people in footage, and checks whether they're wearing masks or not, and keeping their social distance or not. Textual results, for example, look like this:
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100DaysOfML
100 Days Of Machine Learning. New Content in every 1-2 day and projects every week. The massive 100DaysOfML in building
Jupyter Notebook Artificial intelligence related posts
- In A Latest Computer Vision Research, Researchers Propose ShAPO; An End-To-End Method For Joint Multi-Object Detection, 3D Textured Reconstruction, 6D Object Pose, And Size Estimation
- ML Concepts
- Contextual Similarity between a list of n-grams and a website
- A minimal standalone example of diffusion model
- (unguided) Sampling from a diffusion model
- I don't trust papers out of “Top Labs” anymore
- Word embeddings / language models for synonym generation?
Index
What are some of the best open-source Artificial intelligence projects in Jupyter Notebook? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | computervision-recipes | 8,594 |
| 2 | machine-learning-for-trading | 6,019 |
| 3 | nlpaug | 3,429 |
| 4 | Reinforcement-Learning | 3,423 |
| 5 | Data-science | 2,730 |
| 6 | AI-For-Beginners | 1,491 |
| 7 | MEDIUM_NoteBook | 1,426 |
| 8 | machine-learning-experiments | 1,295 |
| 9 | imodels | 875 |
| 10 | cryptocurrency-price-prediction | 477 |
| 11 | 100DaysofMLCode | 246 |
| 12 | elastic_transformers | 148 |
| 13 | Fast-Transformer | 137 |
| 14 | diffusion_models | 126 |
| 15 | conformal_classification | 122 |
| 16 | CenterSnap | 117 |
| 17 | artificial-intelligence-and-machine-learning | 106 |
| 18 | ai-seed | 87 |
| 19 | language-planner | 86 |
| 20 | tabular-dl-num-embeddings | 85 |
| 21 | EfficientWord-Net | 79 |
| 22 | Social_Distancing_with_AI | 57 |
| 23 | 100DaysOfML | 50 |
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