Jupyter Notebook Classification

Open-source Jupyter Notebook projects categorized as Classification
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Topics: Machine Learning Deep Learning Python Data Science Computer Vision
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Top 23 Jupyter Notebook Classification Projects

  • pycaret

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

  • tsai

    Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

    • Project mention: Aeon: A unified framework for machine learning with time series | news.ycombinator.com | 2023-06-22

    Also https://github.com/timeseriesAI/tsai

  • 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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  • 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...

  • MAPIE

    A scikit-learn-compatible module for estimating prediction intervals.

  • Food-Recipe-CNN

    food image to recipe with deep convolutional neural networks.

  • maxvit

    [ECCV 2022] Official repository for "MaxViT: Multi-Axis Vision Transformer". SOTA foundation models for classification, detection, segmentation, image quality, and generative modeling...

  • glasses

    High-quality Neural Networks for Computer Vision 😎

  • 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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  • tiger

    Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning) (by tigerlab-ai)

    • Project mention: FLaNK Stack Weekly for 13 November 2023 | dev.to | 2023-11-13

  • 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).

  • benchmarks

    Comparison tools (by catboost)

  • Network-Intrusion-Detection-Using-Machine-Learning

    A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

  • GatedTabTransformer

    A deep learning tabular classification architecture inspired by TabTransformer with integrated gated multilayer perceptron.

  • tutorial-face-mask-detection

    In this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert people that do not wear a mask when entering a building.

  • glami-1m

    The largest multilingual image-text classification dataset. It contains fashion products.

  • BrewPOTS

    The tutorials for PyPOTS.

    • Project mention: We're building PyPOTS: a Python toolbox for data mining on Partially-Observed Time Series | /r/learnprogramming | 2023-06-19

    Due to all kinds of reasons like failures of collection sensors, communication errors, and unexpected malfunctions, missing values are common to see in time series from the real-world environment. No matter whether we like them or not, missing data makes partially-observed time series (POTS) a pervasive problem in open-world modeling and prevents advanced data analysis. Although this problem is important, the area of data mining on POTS still lacks a dedicated toolkit. PyPOTS is created to fill in this gap. PyPOTS (pronounced "Pie Pots") is the first (and so far the only) Python toolbox/library specifically designed for data mining and machine learning on partially-observed time series (POTS), namely, incomplete time series with missing values, A.K.A. irregularly-sampled time series, supporting tasks of imputation, classification, clustering, and forecasting on POTS datasets. It is born to become a handy toolbox that is going to make data mining on POTS easy rather than tedious, to help engineers and researchers focus more on the core problems in their hands rather than on how to deal with the missing parts in their data. PyPOTS will keep integrating classical and the latest state-of-the-art data mining algorithms for partially-observed multivariate time series. For sure, besides various algorithms, PyPOTS has unified APIs together with detailed documentation and interactive examples across algorithms as tutorials. Feedback, questions, and contributions are all very welcome! Website: https://pypots.com Paper link: https://arxiv.org/abs/2305.18811 GitHub repo: https://github.com/WenjieDu/PyPOTS Tutorials: https://github.com/WenjieDu/BrewPOTS Docs: https://docs.pypots.com

  • data-science-notes

    Notes of IBM Data Science Professional Certificate Courses on Coursera

  • langhuan

    Light weight labeling engine

  • mlscorecheck

    Testing the consistency of binary classification performance scores reported in papers

    • Project mention: [N] (In)validating published ML performance scores is possible | /r/MachineLearning | 2023-11-18

  • Ordinal_Classifier

    Introduce order in your classification within 1 line

  • liga-pytorch

    Let Data Dance with PyTorch Models

  • network-attack-detection

    Advanced detection of port scanning, DoS and malware attacks using Machine Learning techniques

    • Project mention: Network attacks detection using Machine Learning techniques | /r/programming | 2023-05-18

  • catboost-quickstart

    🐈 🚀 Quickstart machine learning notebooks for creating CatBoost models

  • NumberRecognition

    Number Recognizer dengan Flask & Tensorflow, Python dari tulisan tangan HTML5 Canvas

  • SaaSHub

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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 2023-11-18.

Jupyter Notebook Classification related posts

Index

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

Project Stars
1 pycaret 8,385
2 tsai 4,659
3 FLAML 3,663
4 MAPIE 1,150
5 Food-Recipe-CNN 560
6 maxvit 417
7 glasses 413
8 tiger 376
9 conformal_classification 202
10 benchmarks 163
11 Network-Intrusion-Detection-Using-Machine-Learning 97
12 GatedTabTransformer 89
13 tutorial-face-mask-detection 86
14 glami-1m 62
15 BrewPOTS 38
16 data-science-notes 35
17 langhuan 12
18 mlscorecheck 11
19 Ordinal_Classifier 5
20 liga-pytorch 5
21 network-attack-detection 4
22 catboost-quickstart 3
23 NumberRecognition 3

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