Jupyter Notebook scikit-learn

Open-source Jupyter Notebook projects categorized as scikit-learn

Top 23 Jupyter Notebook scikit-learn Projects

scikit-learn
  • PythonDataScienceHandbook

    Python Data Science Handbook: full text in Jupyter Notebooks

    Project mention: Python Data Science Handbook | news.ycombinator.com | 2024-05-19
  • 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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  • handson-ml

    ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

  • python-machine-learning-book

    The "Python Machine Learning (1st edition)" book code repository and info resource

  • skorch

    A scikit-learn compatible neural network library that wraps PyTorch

  • machine_learning_complete

    A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.

  • python-machine-learning-book-3rd-edition

    The "Python Machine Learning (3rd edition)" book code repository

  • FLAML

    A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

    Project mention: AutoGen: Enabling Next-Gen GPT-X Applications | news.ycombinator.com | 2023-08-22

    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...

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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  • ML-Workspace

    🛠 All-in-one web-based IDE specialized for machine learning and data science.

  • machine-learning-book

    Code Repository for Machine Learning with PyTorch and Scikit-Learn

    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.

  • dtreeviz

    A python library for decision tree visualization and model interpretation.

    Project mention: Dtreeviz: Decision Tree Visualization | news.ycombinator.com | 2023-08-03
  • eli5

    A library for debugging/inspecting machine learning classifiers and explaining their predictions

  • hyperlearn

    2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

    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!

  • imodels

    Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

    Project mention: FLaNK-AIM: 20 May 2024 Weekly | dev.to | 2024-05-20
  • code

    Compilation of R and Python programming codes on the Data Professor YouTube channel. (by dataprofessor)

  • human-learn

    Natural Intelligence is still a pretty good idea.

  • linear-tree

    A python library to build Model Trees with Linear Models at the leaves.

  • bert-sklearn

    a sklearn wrapper for Google's BERT model

  • feature-engineering-tutorials

    Data Science Feature Engineering and Selection Tutorials

  • converse

    Conversational text Analysis using various NLP techniques

  • WallStreetBets_BigDataAnalysis

    Research project aimed to classify the best stock research posts from r/WallStreetBets for you. 😏

  • poniard

    Streamline scikit-learn model comparison.

  • fake-news

    Building a fake news detector from initial ideation to model deployment

  • aws-lambda-docker-serverless-inference

    Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

    SaaSHub logo
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).

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Jupyter Notebook scikit-learn related posts

  • Python Data Science Handbook

    1 project | news.ycombinator.com | 19 May 2024
  • Show HN: Logistic Regression Training on Encrypted Data with FHE

    1 project | news.ycombinator.com | 6 Feb 2024
  • Implementing a ChatGPT-like LLM from scratch, step by step

    3 projects | news.ycombinator.com | 27 Jan 2024
  • Training ML Models on Encrypted Data with Homomorphic Encryption (FHE)

    1 project | news.ycombinator.com | 25 Jan 2024
  • Dtreeviz: Decision Tree Visualization

    1 project | news.ycombinator.com | 3 Aug 2023
  • Where to learn data science with python??

    1 project | /r/learnpython | 2 Jul 2023
  • Is there any algorithm that combines decision trees with regression models?

    1 project | /r/learnmachinelearning | 6 Jun 2023
  • A note from our sponsor - InfluxDB
    www.influxdata.com | 20 Jul 2024
    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. Learn more →

Index

What are some of the best open-source scikit-learn projects in Jupyter Notebook? This list will help you:

Project Stars
1 PythonDataScienceHandbook 42,227
2 handson-ml 25,136
3 python-machine-learning-book 12,180
4 skorch 5,704
5 machine_learning_complete 4,555
6 python-machine-learning-book-3rd-edition 4,482
7 FLAML 3,770
8 ML-Workspace 3,366
9 machine-learning-book 3,105
10 dtreeviz 2,892
11 eli5 2,730
12 hyperlearn 1,578
13 imodels 1,342
14 code 893
15 human-learn 788
16 linear-tree 329
17 bert-sklearn 293
18 feature-engineering-tutorials 268
19 converse 176
20 WallStreetBets_BigDataAnalysis 170
21 poniard 146
22 fake-news 130
23 aws-lambda-docker-serverless-inference 94

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