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Top 23 Jupyter Notebook scikit-learn Projects
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Project mention: About Data analyst, data scientist and data engineer, resources and experiences | dev.to | 2024-03-26
Python Data Science Handbook
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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python-machine-learning-book
The "Python Machine Learning (1st edition)" book code repository and info resource
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machine_learning_complete
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
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python-machine-learning-book-3rd-edition
The "Python Machine Learning (3rd edition)" book code repository
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I really like the simplicity of this framework, and they hit on a lot of common problems found in other agent-based frameworks. Most intrigued by the RAG improvements.
Seems like Microsoft was frustrated with the pace of movement in this space and the shitty results of agents (which admittedly kept my interest turned away from agents for the last few months). I'm interested again because it makes practical sense, and from looking at the example notebooks, seems fairly easy to integrate into existing applications.
Maybe this is the 'low code' approach that might actually work, and bridge together engineering and non-engineering resources.
This example was what caught my eye: https://github.com/microsoft/FLAML/blob/main/notebook/autoge...
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Project mention: Implementing a ChatGPT-like LLM from scratch, step by step | news.ycombinator.com | 2024-01-27
Sorry, in that case I would rather recommend a dedicated RL book. The RL part in LLMs will be very specific to LLMs, and I will only cover what's absolutely relevant in terms of background info. I do have a longish intro chapter on RL in my other general ML/DL book (https://github.com/rasbt/machine-learning-book/tree/main/ch1...) but like others said, I would recommend a dedicated RL book in your case.
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eli5
A library for debugging/inspecting machine learning classifiers and explaining their predictions
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Project mention: 80% faster, 50% less memory, 0% loss of accuracy Llama finetuning | news.ycombinator.com | 2023-12-01
Good point - the main issue is we encountered this exact issue with our old package Hyperlearn (https://github.com/danielhanchen/hyperlearn).
I OSSed all the code to the community - I'm actually an extremely open person and I love contributing to the OSS community.
The issue was the package got gobbled up by other startups and big tech companies with no credit - I didn't want any cash from it, but it stung and hurt really bad hearing other startups and companies claim it was them who made it faster, whilst it was actually my work. It hurt really bad - as an OSS person, I don't want money, but just some recognition for the work.
I also used to accept and help everyone with their writing their startup's software, but I never got paid or even any thanks - sadly I didn't expect the world to be such a hostile place.
So after a sad awakening, I decided with my brother instead of OSSing everything, we would first OSS something which is still very good - 5X faster training is already very reasonable.
I'm all open to other suggestions on how we should approach this though! There are no evil intentions - in fact I insisted we OSS EVERYTHING even the 30x faster algos, but after a level headed discussion with my brother - we still have to pay life expenses no?
If you have other ways we can go about this - I'm all ears!! We're literally making stuff up as we go along!
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imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
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code
Compilation of R and Python programming codes on the Data Professor YouTube channel. (by dataprofessor)
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Project mention: How to build a prediction model where there is negligible relation between the target variable and independent variables? | /r/datascience | 2023-05-31
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concrete-ml
Concrete ML: Privacy Preserving ML framework built on top of Concrete, with bindings to traditional ML frameworks.
Project mention: Show HN: Logistic Regression Training on Encrypted Data with FHE | news.ycombinator.com | 2024-02-06 -
Project mention: Is there any algorithm that combines decision trees with regression models? | /r/learnmachinelearning | 2023-06-06
Sure is! Here’s an implementation
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WallStreetBets_BigDataAnalysis
Research project aimed to classify the best stock research posts from r/WallStreetBets for you. 😏
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Jupyter Notebook scikit-learn related posts
- Show HN: Logistic Regression Training on Encrypted Data with FHE
- Implementing a ChatGPT-like LLM from scratch, step by step
- Training ML Models on Encrypted Data with Homomorphic Encryption (FHE)
- Dtreeviz: Decision Tree Visualization
- Where to learn data science with python??
- Is there any algorithm that combines decision trees with regression models?
- Book Recommendations
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www.saashub.com | 28 Mar 2024
Index
What are some of the best open-source scikit-learn projects in Jupyter Notebook? This list will help you:
Project | Stars | |
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1 | PythonDataScienceHandbook | 41,238 |
2 | handson-ml | 25,100 |
3 | python-machine-learning-book | 12,076 |
4 | skorch | 5,596 |
5 | machine_learning_complete | 4,462 |
6 | python-machine-learning-book-3rd-edition | 4,362 |
7 | FLAML | 3,618 |
8 | ML-Workspace | 3,310 |
9 | dtreeviz | 2,804 |
10 | machine-learning-book | 2,764 |
11 | eli5 | 2,708 |
12 | hyperlearn | 1,510 |
13 | imodels | 1,274 |
14 | code | 858 |
15 | human-learn | 770 |
16 | concrete-ml | 730 |
17 | linear-tree | 321 |
18 | bert-sklearn | 289 |
19 | feature-engineering-tutorials | 263 |
20 | converse | 176 |
21 | WallStreetBets_BigDataAnalysis | 167 |
22 | poniard | 145 |
23 | fake-news | 128 |