Jupyter Notebook Machine Learning

Open-source Jupyter Notebook projects categorized as Machine Learning | Edit details

Top 23 Jupyter Notebook Machine Learning Projects

  • GitHub repo TensorFlow-Examples

    TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

    Project mention: Keras vs. TensorFlow | dev.to | 2021-06-06

    A linear regression model

  • GitHub repo MadeWithML

    Learn how to responsibly deliver value with ML.

    Project mention: New to mlops, where do I need to start | reddit.com/r/mlops | 2021-11-01

    Standing recommendation for beginners (we should eventually make a wiki) is https://madewithml.com/

  • OPS

    OPS - Build and Run Open Source Unikernels. Quickly and easily build and deploy open source unikernels in tens of seconds. Deploy in any language to any cloud.

  • GitHub repo ML-For-Beginners

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

    Project mention: Top Github repo trends in 2021 | dev.to | 2022-01-12

    three educational courses- Web Dev, ML, and IoT for beginners. Note re using educational resources as a strategy for marketing , at least the ML course links to various Azure services. Google does this a bunch as well, with Collab notebooks often being used to demo educational materials.

  • GitHub repo fastai

    The fastai deep learning library

    Project mention: Good practices for neural network training: identify, save, and document best models | dev.to | 2022-01-04

    If you are unaware of what fastai is, its official description is:

  • GitHub repo google-research

    Google Research

    Project mention: I'm failing to download a repository correctly | reddit.com/r/u_No_Possibility_7588 | 2022-01-18

    # Install steps - download the `ml-agents` repository `git clone https://github.com/Unity-Technologies/ml-agents` - create a Python folder in `ml-agents` and clone `social_rl` repo into it `svn export https://github.com/google-research/google-research/trunk/social_rl` - copy `environments.py` and `gymwrappers.py` into this Python folder - create a python3.8 environment and install `social_rl` requirements `conda create -n mlagents python=3.8` `pip install -r requirements.txt` - install `ml-agents_envs`, `ml-agents` and `gym-unity` from the `ml-agents` repository `python install setup.py`

  • GitHub repo homemade-machine-learning

    🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

    Project mention: Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained | reddit.com/r/MachineLearning | 2021-10-27
  • GitHub repo shap

    A game theoretic approach to explain the output of any machine learning model.

    Project mention: [Q] What's the community's opinion of "interpretable ML/AI"? | reddit.com/r/statistics | 2022-01-14

    I've become a zealot about parametric stats, specifically from the Bayesian paradigm. Something about studying the core business problem, choosing the best distribution(s), and making inferences has been really rewarding for me. But increasingly, I'm seeing tools like SHAP, which allegedly enable users of black-box ML models to intuit what/how their models "think". (SHAP is just one example.)

  • SonarLint

    Deliver Cleaner and Safer Code - Right in Your IDE of Choice!. SonarLint is a free and open source IDE extension that identifies and catches bugs and vulnerabilities as you code, directly in the IDE. Install from your favorite IDE marketplace today.

  • GitHub repo fastbook

    The fastai book, published as Jupyter Notebooks

    Project mention: Starting a career as a Python developer | reddit.com/r/learnpython | 2021-12-20

    I’m a fan of fast book by fastai.

  • GitHub repo python-machine-learning-book

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

    Project mention: What is the purpose of meshgrid in Python / NumPy? | reddit.com/r/codehunter | 2022-01-06

    I am studying "Python Machine Learning" from Sebastian Raschka, and he is using it for plotting the decision borders. See input 11 here.

  • GitHub repo TensorFlow-Tutorials

    TensorFlow Tutorials with YouTube Videos

    Project mention: Plagiarism is just bad | reddit.com/r/github | 2021-02-20

    The majority of this code is taken from the TensorFlow-Tutorials. I highly recommend them to those who want to get started with TensorFlow.

  • GitHub repo pandas-profiling

    Create HTML profiling reports from pandas DataFrame objects

    Project mention: Day 2: Fancy packages to work with Dataframe | dev.to | 2021-12-28

    2 packages I want to mention is pandas-profiling and Mito.

  • GitHub repo amazon-sagemaker-examples

    Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

    Project mention: AWS - NLP newsletter November 2021 | dev.to | 2021-11-24

    Amazon SageMaker Asynchronous Inference with Hugging Face Model Amazon SageMaker Asynchronous Inference is a new capability in SageMaker that queues incoming requests and processes them asynchronously. SageMaker currently offers two inference options for customers to deploy machine learning models: 1) a real-time option for low-latency workloads 2) Batch transform, an offline option to process inference requests on batches of data available upfront. Real-time inference is suited for workloads with payload sizes of less than 6 MB and require inference requests to be processed within 60 seconds. Batch transform is suitable for offline inference on batches of data. This notebook provides an introduction on how to use the SageMaker Asynchronous inference capability with Hugging Face models. This notebook will cover the steps required to create an Asynchronous inference endpoint and test it with some sample requests.

  • GitHub repo swift

    Swift for TensorFlow (by tensorflow)

    Project mention: Engineering Trade-Offs in Automatic Differentiation: from TensorFlow and PyTorch to Jax and Julia - Stochastic Lifestyle | reddit.com/r/programming | 2021-12-26

    Apple really is focusing on CoreML rather than differentiable swift, that was more of the vision of Swift4TF, which really was driven mostly by Google, until it was cancelled (I assume because of Chris Latner leaving google for SiFive): https://github.com/tensorflow/swift

  • GitHub repo H2O

    H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

    Project mention: [PAID] Looking for Phaser.js game developer | reddit.com/r/INAT | 2021-12-09

    Built and founded various web3 projects for last 2 years such as OpenArt and 8RealmDojo for last 2 years as well as being high performing student in CTU in Prague and SeoulTech. Was offered internships in Amazon and H2O.ai. Created robots assistants using robots from SoftBank.

  • GitHub repo cleverhans

    An adversarial example library for constructing attacks, building defenses, and benchmarking both

  • GitHub repo machine-learning-for-trading

    Code for Machine Learning for Algorithmic Trading, 2nd edition.

    Project mention: Machine Learning for Trading: Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading. Courses - star count:5136.0 | reddit.com/r/algoprojects | 2022-01-21
  • GitHub repo docs

    TensorFlow documentation (by tensorflow)

    Project mention: Anyone willing to help me out on a discord call or something? | reddit.com/r/learnmachinelearning | 2021-05-27

    This is the model I’m trying to understand and create my own version of: https://github.com/tensorflow/docs/blob/master/site/en/r1/tutorials/sequences/recurrent_quickdraw.md

  • GitHub repo pycaret

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

    Project mention: Pycaret | news.ycombinator.com | 2021-12-28
  • GitHub repo lucid

    A collection of infrastructure and tools for research in neural network interpretability.

    Project mention: [D] Open source projects for interpretability | reddit.com/r/MachineLearning | 2021-04-28

    You should check out Captum for PyTorch: https://captum.ai/ and tf-explain or lucid (this one is the framework used by distill) for Tensorflow although I think they are both oriented towards Vision interpretability (not sure if you are looking for that).

  • GitHub repo skorch

    A scikit-learn compatible neural network library that wraps PyTorch

    Project mention: [P] ray-skorch - distributed PyTorch on Ray with sklearn API | reddit.com/r/MachineLearning | 2022-01-04

    I'm the principal author of ray-skorch, a library that lets you run distributed PyTorch training on large-scale datasets while providing a familiar, scikit-learn compatible skorch API, integrating well with the rest of the scikit-learn ecosystem.

  • GitHub repo t81_558_deep_learning

    Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

    Project mention: Different Outputs on Mac M1 and Windows | reddit.com/r/tensorflow | 2021-11-26
  • GitHub repo machine_learning_basics

    Plain python implementations of basic machine learning algorithms

    Project mention: Bayesian linear regression in (plain) Python | reddit.com/r/Python | 2021-01-29

    A while back I open sourced a repository implementing fundamental machine learning algorithms in Python, along with the most important theoretical information. I originally created the repository for myself when preparing for AI residency interviews. You can find the original Reddit post here.

  • GitHub repo probability

    Probabilistic reasoning and statistical analysis in TensorFlow

    Project mention: What is Probabilistic Programming? | reddit.com/r/learnmachinelearning | 2021-09-06

    This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are - Stan (https://mc-stan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arviz-devs.github.io/arviz/), which can be used for all the above-mentioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing

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 2022-01-21.

Jupyter Notebook Machine Learning related posts

Index

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

Project Stars
1 TensorFlow-Examples 41,601
2 MadeWithML 29,409
3 ML-For-Beginners 28,735
4 fastai 21,844
5 google-research 21,522
6 homemade-machine-learning 18,774
7 shap 15,176
8 fastbook 14,148
9 python-machine-learning-book 11,460
10 TensorFlow-Tutorials 8,941
11 pandas-profiling 8,415
12 amazon-sagemaker-examples 6,433
13 swift 6,038
14 H2O 5,691
15 cleverhans 5,381
16 machine-learning-for-trading 5,147
17 docs 5,045
18 pycaret 4,943
19 lucid 4,360
20 skorch 4,302
21 t81_558_deep_learning 4,232
22 machine_learning_basics 3,594
23 probability 3,571
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