Jupyter Notebook ML

Open-source Jupyter Notebook projects categorized as ML

Top 23 Jupyter Notebook ML Projects

  • ML-For-Beginners

    12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

    Project mention: I want to learn more about AI and Machine Learning | reddit.com/r/ArtificialInteligence | 2023-01-12
  • handson-ml

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

    Project mention: need a book recommendation for machine learning on python | reddit.com/r/learnpython | 2022-05-25

    Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is often recommended. You can check out the GitHub repo first: https://github.com/ageron/handson-ml

  • 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.

  • dopamine

    Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

    Project mention: RL review | reddit.com/r/reinforcementlearning | 2022-10-24

    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”.

  • pycaret

    An open-source, low-code machine learning library in Python

    Project mention: pycaret: An open-source, low-code machine learning library in Python | reddit.com/r/coolgithubprojects | 2022-09-13
  • nlpaug

    Data augmentation for NLP

    Project mention: Use WordNet to collect homonyms | reddit.com/r/LanguageTechnology | 2022-09-23

    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.

  • CodeSearchNet

    Datasets, tools, and benchmarks for representation learning of code.

  • imodels

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

    Project mention: What would be my best approach given the data I have? | reddit.com/r/datascience | 2022-10-17

    Next, this variable will be your target and you can use various supervised learning models to answer your question. Since interpretation is key, you can use something from here: https://github.com/csinva/imodels or do some black box models and use shab to understand which features contributed most.

  • 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.

  • azureml-examples

    Official community-driven Azure Machine Learning examples, tested with GitHub Actions.

  • vertex-ai-samples

    Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

    Project mention: JBCNConf 2022: A great farewell | dev.to | 2022-07-23

    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

  • 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
  • chatgpt-comparison-detection

    Human ChatGPT Comparison Corpus (HC3), Detectors, and more! 🔥

    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! 🔥

  • serverless-ml-course

    Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features

    Project mention: Serverless Video Transcription inspired by Cyberpunk 2077 | news.ycombinator.com | 2022-12-22


    Some of the students have built similar systems, for example chaining Whisper and ChatGPT or translation or sentiment analysis of transcribed text, such as here (transcribe Swedish and tell me the sentiment of the text):

  • S2ML-Generators

    Multiple notebooks which allow the use of various machine learning methods to generate or modify multimedia content

    Project mention: Sense of AI | Vqgan+Clip | reddit.com/r/MediaSynthesis | 2022-02-09

    At default settings_ https://github.com/justin-bennington/S2ML-Generators

  • gan-vae-pretrained-pytorch

    Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

    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.

  • examples

    📝 Examples of experiment tracking, model registry, data versioning, and monitoring machine learning model training live in neptune.ai (by neptune-ai)

    Project mention: examples: 📝 Examples of experiment tracking, model registry, data versioning, and monitoring machine learning model training live in neptune.ai | reddit.com/r/u_TsukiZombina | 2023-01-13
  • ltt

    Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

    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 | 2022-03-06

    ​Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control https://arxiv.org/abs/2110.01052 https://github.com/aangelopoulos/ltt

  • creative-prediction

    Creative Prediction with Neural Networks

  • Projects-Archive

    This hacktober fest, the only stop you’ll need to make for ML, Web Dev and App Dev - see you there!

  • Computer-Science-Resources

    This repository aims at providing the best resources for computer science students at one place. So they don't have to waste their precious time finding good resources. (by shivanshsinghx365)

    Project mention: I have Created a repository for good resources for "Computer Science" for hacktober fest, interested people may contribute | reddit.com/r/hacktoberfest | 2022-09-26

    here's the link for the same : https://github.com/shivanshsinghx365/Computer-Science-Resources

  • emb-gam

    An interpretable and efficient predictor using pre-trained language models. Scikit-learn compatible.

    Project mention: [R] Emb-GAM: an Interpretable and Efficient Predictor using Pre-trained Language Models | reddit.com/r/MachineLearning | 2022-10-04

    Deep learning models have achieved impressive prediction performance but often sacrifice interpretability, a critical consideration in high-stakes domains such as healthcare or policymaking. In contrast, generalized additive models (GAMs) can maintain interpretability but often suffer from poor prediction performance due to their inability to effectively capture feature interactions. In this work, we aim to bridge this gap by using pre-trained neural language models to extract embeddings for each input before learning a linear model in the embedding space. The final model (which we call Emb-GAM) is a transparent, linear function of its input features and feature interactions. Leveraging the language model allows Emb-GAM to learn far fewer linear coefficients, model larger interactions, and generalize well to novel inputs (e.g. unseen ngrams in text). Across a variety of NLP datasets, Emb-GAM achieves strong prediction performance without sacrificing interpretability. All code is made available on Github.

  • chappie.ai

    Generalized AI to perform a multitude of tasks written in python3

  • SuiSense

    Using Artificial Intelligence to distinguish between suicidal and depressive messages (4th Place Congressional App Challenge)

  • Understanding_the_EM_Algorithm

    Codes for my blog post "Understanding the EM Algorithm" https://mistylight.github.io/posts/20115/

  • SaaSHub

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

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 2023-01-13.

Jupyter Notebook ML related posts


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

Project Stars
1 ML-For-Beginners 43,860
2 handson-ml 24,961
3 dopamine 9,992
4 pycaret 6,833
5 nlpaug 3,765
6 CodeSearchNet 1,778
7 imodels 1,010
8 azureml-examples 917
9 vertex-ai-samples 577
10 cleora 404
11 chatgpt-comparison-detection 280
12 serverless-ml-course 256
13 S2ML-Generators 177
14 gan-vae-pretrained-pytorch 141
15 examples 36
16 ltt 35
17 creative-prediction 22
18 Projects-Archive 21
19 Computer-Science-Resources 21
20 emb-gam 20
21 chappie.ai 14
22 SuiSense 9
23 Understanding_the_EM_Algorithm 6
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives